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Background: For RCTs with time-to-event endpoints, proportional hazard (PH) models are typically used to estimate treatment effects and logrank tests are commonly used for hypothesis testing. There is growing support for replacing this approach with a model-free estimand and assumption-lean analysis method. One alternative is to base the analysis on the difference in restricted mean survival time (RMST) at a specific time, a single-number summary measure that can be defined without any restrictive assumptions on the outcome model. In a simple setting without covariates, an assumption-lean analysis can be achieved using nonparametric methods such as Kaplan Meier estimation. The main advantage of moving to a model-free summary measure and assumption-lean analysis is that the validity and interpretation of conclusions do not depend on the PH assumption. The potential disadvantage is that the nonparametric analysis may lose efficiency under PH. There is disagreement in recent literature on this issue. Methods: Asymptotic results and simulations are used to compare the efficiency of a log-rank test against a nonparametric analysis of the difference in RMST in a superiority trial under PH. Previous studies have separately examined the effect of event rates and the censoring distribution on relative efficiency. This investigation clarifies conflicting results from earlier research by exploring the joint effect of event rate and censoring distribution together. Several illustrative examples are provided. Results: In scenarios with high event rates and/or substantial censoring across a large proportion of the study window, and when both methods make use of the same amount of data, relative efficiency is close to unity. However, in cases with low event rates but when censoring is concentrated at the end of the study window, the PH analysis has a considerable efficiency advantage.

Comparison studies in methodological research are intended to compare methods in an evidence-based manner, offering guidance to data analysts to select a suitable method for their application. To provide trustworthy evidence, they must be carefully designed, implemented, and reported, especially given the many decisions made in planning and running. A common challenge in comparison studies is to handle the ``failure'' of one or more methods to produce a result for some (real or simulated) data sets, such that their performances cannot be measured in those instances. Despite an increasing emphasis on this topic in recent literature (focusing on non-convergence as a common manifestation), there is little guidance on proper handling and interpretation, and reporting of the chosen approach is often neglected. This paper aims to fill this gap and provides practical guidance for handling method failure in comparison studies. In particular, we show that the popular approaches of discarding data sets yielding failure (either for all or the failing methods only) and imputing are inappropriate in most cases. We also discuss how method failure in published comparison studies -- in various contexts from classical statistics and predictive modeling -- may manifest differently, but is often caused by a complex interplay of several aspects. Building on this, we provide recommendations derived from realistic considerations on suitable fallbacks when encountering method failure, hence avoiding the need for discarding data sets or imputation. Finally, we illustrate our recommendations and the dangers of inadequate handling of method failure through two illustrative comparison studies.

The Fine-Gray model for the subdistribution hazard is commonly used for estimating associations between covariates and competing risks outcomes. When there are missing values in the covariates included in a given model, researchers may wish to multiply impute them. Assuming interest lies in estimating the risk of only one of the competing events, this paper develops a substantive-model-compatible multiple imputation approach that exploits the parallels between the Fine-Gray model and the standard (single-event) Cox model. In the presence of right-censoring, this involves first imputing the potential censoring times for those failing from competing events, and thereafter imputing the missing covariates by leveraging methodology previously developed for the Cox model in the setting without competing risks. In a simulation study, we compared the proposed approach to alternative methods, such as imputing compatibly with cause-specific Cox models. The proposed method performed well (in terms of estimation of both subdistribution log hazard ratios and cumulative incidences) when data were generated assuming proportional subdistribution hazards, and performed satisfactorily when this assumption was not satisfied. The gain in efficiency compared to a complete-case analysis was demonstrated in both the simulation study and in an applied data example on competing outcomes following an allogeneic stem cell transplantation. For individual-specific cumulative incidence estimation, assuming proportionality on the correct scale at the analysis phase appears to be more important than correctly specifying the imputation procedure used to impute the missing covariates.

Derived variables are variables that are constructed from one or more source variables through established mathematical operations or algorithms. For example, body mass index (BMI) is a derived variable constructed from two source variables: weight and height. When using a derived variable as the outcome in a statistical model, complications arise when some of the source variables have missing values. In this paper, we propose how one can define a single fully Bayesian model to simultaneously impute missing values and sample from the posterior. We compare our proposed method with alternative approaches that rely on multiple imputation, and, with a simulated dataset, consider how best to estimate the risk of microcephaly in newborns exposed to the ZIKA virus.

One of the obstacles to reconciling quantum theory with general relativity, is constructing a theory which is both consistent with observation, and and gives finite answers at high energy, so that the theory holds at arbitrarily short distances. Quantum field theory achieves this through the process of renormalisation, but famously, perturbative quantum gravity fails to be renormalisable, even without coupling to matter. Recently, an alternative to quantum gravity has been proposed, in which the geometry of spacetime is taken to be classical rather than quantum, while still being coupled to quantum matter fields [1, 2]. This can be done consistently, provided the dynamics is fundamentally stochastic. Here, we find that the pure gravity theory is formally renormalisable. We do so via the path integral formulation by relating the classical-quantum action to that of quadratic gravity which is renormalisable. Because the action induces stochastic dynamics of space-time, rather than deterministic evolution of a quantum field, the classical-quantum theory is free of tachyons and negative norm ghosts. The key remaining question is whether the renormalisation prescription retains completely positive (CP) dynamics. This consideration appears to single out the scale invariant and asymptotically free theory. We give further evidence that the theory is CP, by showing that the two-point function of the scalar mode is positive. To support the use of precision accelerometers in testing the quantum nature of spacetime, we also compute the power spectral density of the acceleration. The results presented here have a number of implications for inflation, CMB data, and experiments to test the quantum nature of spacetime. They may also provide a way to compute probabilities in the regime of quantum gravity where spacetime can be treated as effectively classical., Comment: v2: PSD pole prescription fand power spectral density for the acceleration added

If the metric is chosen to depend exponentially on the conformal factor, and if one works in a gauge where the conformal factor has the wrong sign propagator, perturbative quantum gravity corrections can be partially resummed into a series of terms each of which is ultraviolet finite. These new terms however are not perturbative in some small parameter, and are not individually BRST invariant, or background diffeomorphism invariant. With appropriate parametrisation, the finiteness property holds true also for a full phenomenologically relevant theory of quantum gravity coupled to (beyond the standard model) matter fields, provided massive tadpole corrections are set to zero by a trivial renormalisation., Comment: 39 pages. Further comments and clarifications added. Version accepted for publication in Jour Class and Quant Gravity

We investigate off-shell perturbative renormalisation of pure quantum gravity for both background metric and quantum fluctuations. We show that at each new loop order, the divergences that do not vanish on-shell are constructed from only the total metric, whilst those that vanish on-shell are renormalised by canonical transformations involving the quantum fields. Purely background metric divergences do not separately appear, and the background metric does not get renormalised. We highlight that renormalisation group identities play a crucial role ensuring consistency in the renormalisation of BRST transformations beyond one loop order. We verify these assertions by computing leading off-shell divergences to two loops, exploiting off-shell BRST invariance and the renormalisation group equations. Although some divergences can be absorbed by field redefinitions, we explain why this does not lead to finite beta-functions for the corresponding field., Comment: 45 pages

We study $d$-dimensional scalar field theory in the Local Potential Approximation of the functional renormalization group. Sturm-Liouville methods allow the eigenoperator equation to be cast as a Schrodinger-type equation. Combining solutions in the large field limit with the Wentzel-Kramers-Brillouin approximation, we solve analytically for the scaling dimension $d_n$ of high dimension potential-type operators $\mathcal{O}_n(\varphi)$ around a non-trivial fixed point. We find that $d_n = n(d-d_\varphi)$ to leading order in $n$ as $n \to \infty$, where $d_\varphi=\frac{1}{2}(d-2+\eta)$ is the scaling dimension of the field, $\varphi$, and determine the power-law growth of the subleading correction. For $O(N)$ invariant scalar field theory, the scaling dimension is just double this, for all fixed $N\geq0$ and additionally for $N=-2,-4,\ldots \,.$ These results are universal, independent of the choice of cutoff function which we keep general throughout, subject only to some weak constraints., Comment: 23 pages, no figures. Clarifications added. Version published in PRD

Background. The DURATIONS design has been recently proposed as a practical alternative to a standard two-arm non-inferiority design when the goal is to optimise some continuous aspect of treatment administration, e.g. duration or frequency, preserving efficacy but improving on secondary outcomes such as safety, costs or convenience. The main features of this design are that (i) it randomises patients to a moderate number of arms across the continuum and (ii) it uses a model to share information across arms. While papers published to date about the design have focused on analysis aspects, here we show how to design such a trial in practice. We use the REFINE-Lung trial as an example; this is a trial seeking the optimal frequency of immunotherapy treatment for non-small cell lung cancer patients. Because the aspect of treatment administration to optimise is frequency, rather than duration, we propose to rename the design as Multi-Arm Multi-Stage Response Over Continuous Intervention (MAMS-ROCI). Methods. We show how simulations can be used to design such a trial. We propose to use the ADEMP framework to plan such simulations, clearly specifying aims, data generating mechanisms, estimands, methods and performance measures before coding and analysing the simulations. We discuss the possible choices to be made using the REFINE-Lung trial as an example. Results. We describe all the choices made while designing the REFINE-Lung trial, and the results of the simulations performed. We justify our choice of total sample size based on these results. Conclusions. MAMS-ROCI trials can be designed using simulation studies that have to be carefully planned and conducted. REFINE-Lung has been designed using such an approach and we have shown how researchers could similarly design their own MAMS-ROCI trial., Comment: 25 pages, 1 table, 5 figures

This article is a review of functional $f(R)$ approximations in the asymptotic safety approach to quantum gravity. It mostly focusses on a formulation that uses a non-adaptive cutoff, resulting in a second order differential equation. This formulation is used as an example to give a detailed explanation for how asymptotic analysis and Sturm-Liouville analysis can be used to uncover some of its most important properties. In particular, if defined appropriately for all values $-\infty

We explore the properties of a recently proposed background independent exact renormalization group approach to gauge theories and gravity. In the process we also develop the machinery needed to study it rigorously. The proposal comes with some advantages. It preserves gauge invariance manifestly, avoids introducing unphysical fields, such as ghosts and Pauli-Villars fields, and does not require gauge-fixing. However, we show that in the simple case of SU(N) Yang-Mills it does not completely regularise the longitudinal part of vertex functions already at one loop, invalidating certain methods for extracting universal components. Moreover we demonstrate a kind of no-go theorem: within the proposed structure, whatever choice is made for covariantisation and cutoff profiles, the two-point vertex flow equation at one loop cannot be both transverse, as required by gauge invariance, and fully regularised., Comment: 51 pages, no figures. Minor corrections. Version published in PRD

Although the biostatistical scientific literature publishes new methods at a very high rate, many of these developments are not trustworthy enough to be adopted by the scientific community. We propose a framework to think about how a piece of methodological work contributes to the evidence base for a method. Similarly to the well-known phases of clinical research in drug development, we define four phases of methodological research. These four phases cover (I) providing logical reasoning and proofs, (II) providing empirical evidence, first in a narrow target setting, then (III) in an extended range of settings and for various outcomes, accompanied by appropriate application examples, and (IV) investigations that establish a method as sufficiently well-understood to know when it is preferred over others and when it is not. We provide basic definitions of the four phases but acknowledge that more work is needed to facilitate unambiguous classification of studies into phases. Methodological developments that have undergone all four proposed phases are still rare, but we give two examples with references. Our concept rebalances the emphasis to studies in phase III and IV, i.e., carefully planned methods comparison studies and studies that explore the empirical properties of existing methods in a wider range of problems., Comment: 14 pages

Selected for the next generation of adaptive optics (AO) systems, the pyramid wavefront sensor (PWFS) is recognised for its closed AO loop performance. As new technologies are emerging, it is necessary to explore new methods to improve it. Microwave Kinetic Inductance Detectors (MKID) are photon-counting devices that measure the arrival time and energy of each incident photon, providing new capabilities over existing detectors and significant AO performance benefits. After developing a multi-wavelength PWFS simulation, we study the benefits of using an energy sensitive detector, analyse the PWFS performance according to wavelength and explore the possibility of using fainter natural guide stars by widening the bandpass of the wavefront sensor., Comment: Proceeding going with presentation done at SPIE 2022, 8 figures, 12 pages

Interactions growing slower than a certain exponential of the square of a scalar field, are well behaved when evolved under the functional renormalization group linearised around the Gaussian fixed point. They satisfy properties usually taken for granted, and reproduce standard perturbative quantisation. However, ever more challenging effects appear the more interactions grow faster than this. We show explicitly that firstly the flow no longer splits uniquely into operators of definite scaling dimension; then (linearised) flows to the infrared can end prematurely in a singularity; and finally new interactions can spontaneously appear at any scale., Comment: 19 pages

Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of alternative methods that utilise large samples of unrelated or related individuals. Yet, specific challenges persist in the estimation of heritability such as epistasis, assortative mating and indirect genetic effects. Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability i.e., the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals (LD score regression, GREML), and family-based genomic designs (Sibling regression, GREML-KIN, Trio-GCTA, MGCTA, RDR). For each method, we describe how heritability is estimated, the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared to samples of related individuals. Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why., Comment: 45 pages, 4 figures

In the analyses of cluster-randomized trials, mixed-model analysis of covariance (ANCOVA) is a standard approach for covariate adjustment and handling within-cluster correlations. However, when the normality, linearity, or the random-intercept assumption is violated, the validity and efficiency of the mixed-model ANCOVA estimators for estimating the average treatment effect remain unclear. Under the potential outcomes framework, we prove that the mixed-model ANCOVA estimators for the average treatment effect are consistent and asymptotically normal under arbitrary misspecification of its working model. If the probability of receiving treatment is 0.5 for each cluster, we further show that the model-based variance estimator under mixed-model ANCOVA1 (ANCOVA without treatment-covariate interactions) remains consistent, clarifying that the confidence interval given by standard software is asymptotically valid even under model misspecification. Beyond robustness, we discuss several insights on precision among classical methods for analyzing cluster-randomized trials, including the mixed-model ANCOVA, individual-level ANCOVA, and cluster-level ANCOVA estimators. These insights may inform the choice of methods in practice. Our analytical results and insights are illustrated via simulation studies and analyses of three cluster-randomized trials.

We study an $f(R)$ approximation to asymptotic safety, using a family of non-adaptive cutoffs, kept general to test for universality. Matching solutions on the four-dimensional sphere and hyperboloid, we prove properties of any such global fixed point solution and its eigenoperators. For this family of cutoffs, the scaling dimension at large $n$ of the $n^\text{th}$ eigenoperator, is $\lambda_n\propto b\, n\ln n$. The coefficient $b$ is non-universal, a consequence of the single-metric approximation. The large $R$ limit is universal on the hyperboloid, but not on the sphere where cutoff dependence results from certain zero modes. For right-sign conformal mode cutoff, the fixed points form at most a discrete set. The eigenoperator spectrum is quantised. They are square integrable under the Sturm-Liouville weight. For wrong sign cutoff, the fixed points form a continuum, and so do the eigenoperators unless we impose square-integrability. If we do this, we get a discrete tower of operators, infinitely many of which are relevant. These are $f(R)$ analogues of novel operators in the conformal sector which were used recently to furnish an alternative quantisation of gravity., Comment: 35 pages, no figures; minor amendments. version published in JHEP

Covariate adjustment has the potential to increase power in the analysis of randomised trials, but mis-specification of the adjustment model could cause error. We explore what error is possible when the adjustment model omits a covariate by randomised treatment interaction, in a setting where the covariate is perfectly balanced between randomised treatments. We use mathematical arguments and analyses of single hypothetical data sets. We show that analysis by a generalised linear model with the canonical link function leads to no error under the null -- that is, if treatment effect is truly zero under the adjusted model then it is also zero under the unadjusted model. However, using non-canonical link functions does not give this property and leads to potentially important error under the null. The error is present even in large samples and hence constitutes bias. We conclude that covariate adjustment analyses of randomised trials should avoid non-canonical links. If a marginal risk difference is the target of estimation then this should not be estimated using an identity link; alternative preferable methods include standardisation and inverse probability of treatment weighting., Comment: 10 pages, 1 figure

Background: It has long been advised to account for baseline covariates in the analysis of confirmatory randomised trials, with the main statistical justifications being that this increases power and, when a randomisation scheme balanced covariates, permits a valid estimate of experimental error. There are various methods available to account for covariates but it is not clear how to choose among them. Methods: Taking the perspective of writing a statistical analysis plan, we consider how to choose between the three most promising broad approaches: direct adjustment, standardisation and inverse-probability-of-treatment weighting. Results: The three approaches are similar in being asymptotically efficient, in losing efficiency with mis-specified covariate functions, and in handling designed balance. If a marginal estimand is targeted (for example, a risk difference or survival difference), then direct adjustment should be avoided because it involves fitting non-standard models that are subject to convergence issues. Convergence is most likely with IPTW. Robust standard errors used by IPTW are anti-conservative at small sample sizes. All approaches can use similar methods to handle missing covariate data. With missing outcome data, each method has its own way to estimate a treatment effect in the all-randomised population. We illustrate some issues in a reanalysis of GetTested, a randomised trial designed to assess the effectiveness of an electonic sexually-transmitted-infection testing and results service. Conclusions: No single approach is always best: the choice will depend on the trial context. We encourage trialists to consider all three methods more routinely., Comment: 1 figure, 5 main tables, 2 appendices, 2 appendix tables

We present the first on-sky results of the micro-lens ring tip-tilt (MLR-TT) sensor. This sensor utilizes a 3D printed micro-lens ring feeding six multi-mode fibers to sense misaligned light, allowing centroid reconstruction. A tip-tilt mirror allows the beam to be corrected, increasing the amount of light coupled into a centrally positioned single-mode (science) fiber. The sensor was tested with the iLocater acquisition camera at the Large Binocular Telescope in November 2019. The limit on the maximum achieved root mean square reconstruction accuracy was found to be 0.19 $\lambda$/D in both tip and tilt, of which approximately 50% of the power originates at frequencies below 10 Hz. We show the reconstruction accuracy is highly dependent on the estimated Strehl ratio and simulations support the assumption that residual adaptive optics aberrations are the main limit to the reconstruction accuracy. We conclude that this sensor is ideally suited to remove post-adaptive optics non-common path tip tilt residuals. We discuss the next steps for the concept development, including optimizations of the lens and fiber, tuning of the correction algorithm and selection of optimal science cases., Comment: Accepted for publication in Journal of the Optical Society of America B (JOSA B)

MOSAIC is the planned multi-object spectrograph for the 39m Extremely Large Telescope (ELT). Conceived as a multi-purpose instrument, it offers both high multiplex and multi-IFU capabilities at a range of intermediate to high spectral resolving powers in the visible and the near-infrared. MOSAIC will enable unique spectroscopic surveys of the faintest sources, from the oldest stars in the Galaxy and beyond to the first populations of galaxies that completed the reionisation of the Universe--while simultaneously opening up a wide discovery space. In this contribution we present the status of the instrument ahead of Phase B, showcasing the key science cases as well as introducing the updated set of top level requirements and the adopted architecture. The high readiness level will allow MOSAIC to soon enter the construction phase, with the goal to provide the ELT community with a world-class MOS capability as soon as possible after the telescope first light., Comment: Accepted to SPIE

HIRES will be the high-resolution spectrograph of the European Extremely Large Telescope at optical and near-infrared wavelengths. It consists of three fibre-fed spectrographs providing a wavelength coverage of 0.4-1.8 mic (goal 0.35-1.8 mic) at a spectral resolution of ~100,000. The fibre-feeding allows HIRES to have several, interchangeable observing modes including a SCAO module and a small diffraction-limited IFU in the NIR. Therefore, it will be able to operate both in seeing and diffraction-limited modes. ELT-HIRES has a wide range of science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Some of the top science cases will be the detection of bio signatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars (PopIII), tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The HIRES consortium is composed of more than 30 institutes from 14 countries, forming a team of more than 200 scientists and engineers., Comment: to appear in the ESO Messenger No.182, December 2020

Direct imaging instruments have the spatial resolution to resolve exoplanets from their host star. This enables direct characterization of the exoplanets atmosphere, but most direct imaging instruments do not have spectrographs with high enough resolving power for detailed atmospheric characterization. We investigate the use of a single-mode diffraction-limited integral-field unit that is compact and easy to integrate into current and future direct imaging instruments for exoplanet characterization. This achieved by making use of recent progress in photonic manufacturing to create a single-mode fiber-fed image reformatter. The fiber-link is created with 3D printed lenses on top of a single-mode multi-core fiber that feeds an ultrafast laser inscribed photonic chip that reformats the fiber into a pseudo-slit. We then couple it to a first-order spectrograph with a triple stacked volume phase holographic grating for a high efficiency over a large bandwidth. The prototype system has had a successful first-light observing run at the 4.2 meter William Herschel Telescope. The measured on-sky resolving power is between 2500 and 3000, depending on the wavelength. With our observations we show that single-mode integral-field spectroscopy is a viable option for current and future exoplanet imaging instruments., Comment: submitted to JATIS

We show that perturbative quantum gravity based on the Einstein-Hilbert action, has a novel continuum limit. The renormalized trajectory emanates from the Gaussian fixed point along (marginally) relevant directions but enters the diffeomorphism invariant subspace only well below a dynamically generated scale. We show that for pure quantum gravity to second order in perturbation theory, and with vanishing cosmological constant, the result is the same as computed in the standard quantisation. Although this case is renormalizable at second order for kinematic reasons, the structure we uncover works in general. One possibility is that gravity has a genuine consistent continuum limit even though it has an infinite number couplings. However we also suggest a possible non-perturbative mechanism, based on the parabolic properties of these flow equations, which would fix all higher order couplings in terms of Newton's constant and the cosmological constant., Comment: 48 pages. 1 figure. 8 more pages with clarifications and new section on gauge parameter (in)dependence. To be publ in CQG

Recently a novel perturbative continuum limit for quantum gravity has been proposed and demonstrated to work at first order. Every interaction monomial $\sigma$ is dressed with a coefficient function $f^\sigma_\Lambda(\varphi)$ of the conformal factor field, $\varphi$. Each coefficient function is parametrised by an infinite number of underlying couplings, and decays at large $\varphi$ with a characteristic amplitude suppression scale which can be chosen to be at a common value, $\Lambda_\text{p}$. Although the theory is perturbative in couplings it is non-perturbative in $\hbar$. At second order in perturbation theory, one must sum over all melonic Feynman diagrams to obtain the particular integral. We show that it leads to a well defined renormalized trajectory and thus continuum limit, provided it is solved by starting at an arbitrary cutoff scale $\Lambda=\mu$ which lies in the range $0<\mu

Latency in the control loop of adaptive optics (AO) systems can severely limit performance. Under the frozen flow hypothesis linear predictive control techniques can overcome this, however identification and tracking of relevant turbulent parameters (such as wind speeds) is required for such parametric techniques. This can complicate practical implementations and introduce stability issues when encountering variable conditions. Here we present a nonlinear wavefront predictor using a Long Short-Term Memory (LSTM) artificial neural network (ANN) that assumes no prior knowledge of the atmosphere and thus requires no user input. The ANN is designed to predict the open-loop wavefront slope measurements of a Shack-Hartmann wavefront sensor (SH-WFS) one frame in advance to compensate for a single-frame delay in a simulated $7\times7$ single-conjugate adaptive optics (SCAO) system operating at 150 Hz. We describe how the training regime of the LSTM ANN affects prediction performance and show how the performance of the predictor varies under various guide star magnitudes. We show that the prediction remains stable when both wind speed and direction are varying. We then extend our approach to a more realistic two-frame latency system. AO system performance when using the LSTM predictor is enhanced for all simulated conditions with prediction errors within 19.9 to 40.0 nm RMS of a latency-free system operating under the same conditions compared to a bandwidth error of $78.3\pm4.4$ nm RMS.

A manifestly diffeomorphism invariant exact renormalization group requires extra diffeomorphism invariant ultraviolet regularisation at some effective cutoff scale $\Lambda$. This motivates construction of a `Parisi-Sourlas' supergravity, in analogy with the gauge theory case, where the superpartner fields have the wrong spin-statistics such that they can become Pauli-Villars regulator fields after spontaneous symmetry breaking. We show that in contrast to gauge theory, the free theory around flat space is already non-trivial and in a sense already displays some spontaneous symmetry breaking. We show that the fluctuating fields form multiplets whose mass matrices imply that the fields propagate into each other not only with the expected $1/p^2$ but also through propagators with improved ultraviolet properties, namely $1/p^4$ and $1/p^6$, despite the fact that the action contains a maximum of two space-time derivatives., Comment: 30 pages. Corrected typos. Further explained our strategy and relation to standard supergravity. Version accepted for Classical & Quantum Gravity

In this paper we study approaches for dealing with treatment when developing a clinical prediction model. Analogous to the estimand framework recently proposed by the European Medicines Agency for clinical trials, we propose a `predictimand' framework of different questions that may be of interest when predicting risk in relation to treatment started after baseline. We provide a formal definition of the estimands matching these questions, give examples of settings in which each is useful and discuss appropriate estimators including their assumptions. We illustrate the impact of the predictimand choice in a dataset of patients with end-stage kidney disease. We argue that clearly defining the estimand is equally important in prediction research as in causal inference., Comment: under review

The Wilsonian renormalization group (RG) properties of the conformal factor of the metric are profoundly altered by the fact that it has a wrong-sign kinetic term. The result is a novel perturbative continuum limit for quantum gravity, which is however non-perturbative in $\hbar$. The ultraviolet part of the renormalized trajectory lies outside the diffeomorphism invariant subspace, entering this subspace only in the infrared, below a dynamically generated amplitude suppression scale. Interactions are dressed with coefficient functions of the conformal factor, their form being determined by the RG. In the ultraviolet, the coefficient functions are parametrised by an infinite number of underlying couplings. Choosing these couplings appropriately, the coefficient functions trivialise on entering the diffeomorphism invariant subspace. Here, dynamically generated effective diffeomorphism couplings emerge, including Newton's constant. In terms of the Legendre effective action, we establish the continuum limit to first order, characterising the most general form of such coefficient functions so as to verify universality., Comment: 47 pages, 2 figures; Expanded version including discussion section. Version to be publ in JHEP

Modern extreme adaptive optics (AO) systems achieving diffraction-limited performance open up new possibilities for instrumentation. Especially important for the fields of spectroscopy and interferometry is that it enables the prospect to couple light into single-mode fibers (SMFs). However, due to their small size, efficient coupling is very sensitive to the quality of the fiber alignment, beam drifts and higher-frequency tip-tilt aberrations caused by telescope mechanics and vibrations. These residual aberrations are not always sensed and corrected by the AO system, leading to unacceptable losses. This is particularly severe for the Extremely Large Telescopes, where their huge structure will mean vibrations increase and optimal AO solutions are even more difficult to implement. We have created a focal plane sensor to correct for residual aberrations by surrounding the SMF with six Multi-mode fibers (MMFs). On each of the MMFs sits a printed freeform lens, making up a six-element micro-lens ring to refract the light into these surrounding MMFs and thus minimizing light loss in the gap between the fiber cores. This means when the beam is near diffraction limited and centered almost all light couples to the SMF. When the beam is misaligned, it couples to the surrounding cores, which are read out by a detector and processed by the DARC software driving a tip-tilt mirror. Currently we are aiming to detect and correct only tip-tilt aberrations. However, choosing to surround the central fiber with six sensing locations potentially allows us to investigate higher order correction modes. Here we present the design and performance our prototype system. This has been designed for use with the iLocater fiber injection system at the LBT and can easily be scaled to larger telescopes. We present test results from the KOOL laboratory and initial integration with the iLocater instrument., Comment: AO4ELT6 Conference Proceedings, 7 pages, 4 figures

Simulation studies allow us to explore the properties of statistical methods. They provide a powerful tool with a multiplicity of aims; among others: evaluating and comparing new or existing statistical methods, assessing violations of modelling assumptions, helping with the understanding of statistical concepts, and supporting the design of clinical trials. The increased availability of powerful computational tools and usable software has contributed to the rise of simulation studies in the current literature. However, simulation studies involve increasingly complex designs, making it difficult to provide all relevant results clearly. Dissemination of results plays a focal role in simulation studies: it can drive applied analysts to use methods that have been shown to perform well in their settings, guide researchers to develop new methods in a promising direction, and provide insights into less established methods. It is crucial that we can digest relevant results of simulation studies. Therefore, we developed INTEREST: an INteractive Tool for Exploring REsults from Simulation sTudies. The tool has been developed using the Shiny framework in R and is available as a web app or as a standalone package. It requires uploading a tidy format dataset with the results of a simulation study in R, Stata, SAS, SPSS, or comma-separated format. A variety of performance measures are estimated automatically along with Monte Carlo standard errors; results and performance summaries are displayed both in tabular and graphical fashion, with a wide variety of available plots. Consequently, the reader can focus on simulation parameters and estimands of most interest. In conclusion, INTEREST can facilitate the investigation of results from simulation studies and supplement the reporting of results, allowing researchers to share detailed results from their simulations and readers to explore them freely.

We show that the Quantum Master Equation and the Wilsonian renormalization group (RG) flow equation can be combined such that for the continuum effective action, quantum BRST invariance is not broken by the presence of an effective ultraviolet cutoff $\Lambda$, despite the fact that the structure demands quantum corrections that naively break the gauge invariance, such as a mass term for a non-Abelian gauge field. Exploiting the derivative expansion, BRST cohomological methods fix the solution up to choice of renormalization conditions, without inputting the form of the classical, or bare, interactions. Legendre transformation results in an equivalent description in terms of solving the modified Slavnov-Taylor identities and the flow of the Legendre effective action under an infrared cutoff $\Lambda$ (i.e. effective average action). The flow generates a canonical transformation that automatically solves the Slavnov-Taylor identities for the wavefunction renormalization constants. We confirm this structure in detail at tree level and one loop. Under flow of $\Lambda$, the standard results are obtained for the beta function, anomalous dimension, and physical amplitudes, up to choice of renormalization scheme., Comment: 58 pages, one figure; Added comments to make clear where the work is (non)perturbative in coupling and Planck's constant. Version to be published in PTEP

Closed-loop adaptive optics systems which use minimum mean square error wavefront reconstruction require the computation of pseudo open loop wavefront slopes. These techniques incorporate a knowledge of atmospheric statistics which must therefore be represented within the wavefront slope measurements. These pseudo open loop slopes are computed from the sum of the measured residual slopes and the reconstructed slopes that would be given if the deformable mirror was flat, generally involving the multiplication of an interaction matrix with actuator demands from the previous time-step. When using dense algebra, this multiplication is computationally expensive for Extremely Large Telescopes, requiring a large memory bandwidth. Here we show that this requirement can be significantly reduced, maintaining mathematical correctness and significantly reducing system complexity. This therefore reduces the cost of these systems and increases robustness and reliability., Comment: Accepted for publication in MNRAS

The Effective Average Action is a form of effective action which depends on a cutoff scale suppressing the contribution of low momentum modes in the functional integral. It reduces to the ordinary effective action when the cutoff scale goes to zero. We derive the modifications of the scale Ward identity due to this cutoff and show how the resulting identity then intimately relates the trace anomaly to the Wilsonian realisation of the renormalization group., Comment: 23 pages, 2 figures; references added + extra discussion. Version to appear in PRD

One of the most useful techniques in astronomical instrumentation is image slicing. It enables a spectrograph to have a more compact angular slit, whilst retaining throughput and increasing resolving power. Astrophotonic components like the photonic lanterns and photonic reformatters can be used to replace bulk optics used so far. This study investigates the performance of such devices using end-to-end simulations to approximate realistic on-sky conditions. It investigates existing components, tries to optimize their performance and aims to understand better how best to design instruments to maximize their performance. This work complements the recent work in the field and provides an estimation for the performance of the new components., Comment: Conference proceedings in SPIE 2018 Austin Texas

We show that the Wilsonian renormalization group (RG) provides a natural regularisation of the Quantum Master Equation such that to first order the BRST algebra closes on local functionals spanned by the eigenoperators with constant couplings. We then apply this to quantum gravity. Around the Gaussian fixed point, RG properties of the conformal factor of the metric allow the construction of a Hilbert space $\mathfrak{L}$ of renormalizable interactions, non-perturbative in $\hbar$, and involving arbitrarily high powers of the gravitational fluctuations. We show that diffeomorphism invariance is violated for interactions that lie inside $\mathfrak{L}$, in the sense that only a trivial quantum BRST cohomology exists for interactions at first order in the couplings. However by taking a limit to the boundary of $\mathfrak{L}$, the couplings can be constrained to recover Newton's constant, and standard realisations of diffeomorphism invariance, whilst retaining renormalizability. The limits are sufficiently flexible to allow this also at higher orders. This leaves open a number of questions that should find their answer at second order. We develop much of the framework that will allow these calculations to be performed., Comment: 64 pages

Multiple imputation (MI) has become popular for analyses with missing data in medical research. The standard implementation of MI is based on the assumption of data being missing at random (MAR). However, for missing data generated by missing not at random (MNAR) mechanisms, MI performed assuming MAR might not be satisfactory. For an incomplete variable in a given dataset, its corresponding population marginal distribution might also be available in an external data source. We show how this information can be readily utilised in the imputation model to calibrate inference to the population, by incorporating an appropriately calculated offset termed the `calibrated-$\delta$ adjustment'. We describe the derivation of this offset from the population distribution of the incomplete variable and show how in applications it can be used to closely (and often exactly) match the post-imputation distribution to the population level. Through analytic and simulation studies, we show that our proposed calibrated-$\delta$ adjustment MI method can give the same inference as standard MI when data are MAR, and can produce more accurate inference under two general MNAR missingness mechanisms. The method is used to impute missing ethnicity data in a type 2 diabetes prevalence case study using UK primary care electronic health records, where it results in scientifically relevant changes in inference for non-White ethnic groups compared to standard MI. Calibrated-$\delta$ adjustment MI represents a pragmatic approach for utilising available population-level information in a sensitivity analysis to explore potential departure from the MAR assumption.

The Wilsonian renormalization group (RG) requires Euclidean signature. The conformal factor of the metric then has a wrong-sign kinetic term, which has a profound effect on its RG properties. In particular around the Gaussian fixed point, it supports a Hilbert space of renormalizable interactions involving arbitrarily high powers of the gravitational fluctuations. These interactions are characterised by being exponentially suppressed for large field amplitude, perturbative in Newton's constant but non-perturbative in Planck's constant. By taking a limit to the boundary of the Hilbert space, diffeomorphism invariance is recovered whilst retaining renormalizability. Thus the so-called conformal factor instability points the way to constructing a perturbatively renormalizable theory of quantum gravity., Comment: 5 pages; Received Honourable mention in Gravity Research Foundation essay competition-2018