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David Wright

Publications and source records attributed to David Wright.

At least 19 recordsLinked to original sources

Mitigating the Timing Impact of Anomalous Pulse Profile Shape Variability in PSR J1713+0747 with Gaussian Component Modeling

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) achieves sub-microsecond timing precision for several millisecond pulsars in its pulsar timing array (PTA) with the objective of detecting and characterizing nanohertz gravitational waves. PSR J1713+0747 is one of the most precisely timed pulsars in the array, achieving sub-microsecond timing precision. However, in April 2021, PSR J1713+0747 underwent a sudden and unusual change in pulse shape that disrupted its timing stability. As PSR J1713+0747 is a key contributor to PTA sensitivity, variations in its pulse profile significantly affect the array's sensitivity to nanohertz gravitational waves. We apply frequency-dependent Gaussian component models to decompose the pulse profile and track the evolution of individual components through the event. This component-level method maintains phase-connected timing across the shape-change event. At L-band, the recovered TOAs have a median uncertainty of ~0.47 microseconds compared to ~0.69 microseconds for standard template matching. At 820 MHz, where profile evolution is stronger, the recovered TOAs have a median uncertainty of ~1.63 microseconds compared to ~0.67 microseconds for standard template matching. The recovered TOAs achieve timing uncertainties comparable to conventional template matching while allowing data affected by profile variability to be retained in PTA gravitational-wave analyses. These results represent an initial step toward profile-domain timing methods capable of accounting for pulse-profile evolution while reducing the need for additional timing model parameters.

astro-ph.HE

Space-based Missile Defense

This paper reviews the technical issues underlying space-based boost-phase missile defense and examines the current technology available for space-based interceptors and the characteristics of the missiles such a system would face. It then analyzes a particular space-based missile defense system that has been proposed to intercept in boost, ascent, and midcourse phases to illustrate the details of such an analysis and the constraints imposed on such systems by the physics of operating in space.

physics.soc-ph

Communicating results in trials with multiple hypotheses or adaptive design features

Over time, clinical trials have increasingly incorporated complex design and analysis elements such as interim analyses, adaptations, multiple endpoints, and sophisticated multiplicity schemes for multiple endpoints and/or treatment arms following the paradigm of frequentist inference. In frequentist clinical trials multiplicity can come from (at least) four sources: multiple looks at the data, multiple endpoints, multiple populations, or multiple treatment comparisons. Normally, Type 1 error control across the multiple hypotheses is implemented to control chance of false positive decisions. To achieve this advanced techniques such as adaptive designs or graphical multiple testing procedures have been developed and are used in the design of clinical trials. However, these methods focus on hypothesis testing while subsequent estimation remains crucial to allow for a benefit-risk assessment and further use of the results by various stakeholders. Through examples, we illustrate challenges in estimation and transparent communication. In general, there are no simple solutions to this conceptual and communicational challenge. The purpose of this paper is to generate awareness of these issues and initiate a discussion about how to address them moving forward.

stat.ME

Estimands and the Choice of Non-Inferiority Margin under ICH E9(R1)

Since the release of the ICH E9(R1) addendum on estimands, its application in non-inferiority trials has received far less attention than in superiority settings. A key conclusion from Lynggaard et al. was that the "choice of non-inferiority margin must reflect the chosen estimand." However, current regulatory guidance predates ICH E9(R1) and therefore does not reflect how the estimand influences the historical evidence and constancy assumption (assay sensitivity) used to derive the non-inferiority margin. This paper investigates the degree to which the non-inferiority margin depends on the estimand. Using simulated patient journeys in a weight-management setting, we illustrate how different intercurrent event strategies and variations in the intercurrent event frequency affect the estimand, and consequently the estimated treatment effect. These results emphasize that the historical treatment effect of the reference treatment versus placebo, and thus the margin $M_{1}$, is specific to an estimand and may differ even when trials formally target similar questions. We further illustrate the process of determining the non-inferiority margin using two examples in non-inferiority trials for a new theoretical weight management treatment. In the first example, we focus on the setting where the historical clinical trials use the estimand framework highlighting that even when they include the estimand framework, determining the non-inferiority margin can be challenging in case the historical trials target an estimand different from the one in the planned study. A second example highlights challenges when historical trials did not employ the estimand framework and the targeted estimand cannot be fully reconstructed.

stat.AP

Statistical Methodology Groups in the Pharmaceutical Industry

Research and Development is the largest budget position in the pharmaceutical industry, with clinical trials being a critical, yet costly and time-consuming component to inform decisions. Beyond drug efficacy, the probability of success and efficiency of research and development are highly dependent on the approaches used for designing, analyzing, and interpreting clinical trials. Deep understanding of statistical methodology and quantitative approaches is therefore essential. Consequently, dedicated methodology groups have emerged in mid-size and large pharmaceutical companies and CROs. Their remit is to lead the conception and implementation of innovative quantitative methodologies in order to improve drug development, often by addressing complexities or offering more efficient designs. To achieve this, they collaborate internally and externally (e.g., with academics, regulators) to identify common challenges and tear down silos in order to invest in methods with the highest impact on efficiency and value to the portfolio. Given the immense financial stakes of drug development -- where delays carry massive implications -- these groups represent a critical strategic investment. However, to realize this business impact, statistical innovations must be rigorously validated and seamlessly integrated. This manuscript explores the setup, remit, and value of dedicated methodology groups, alongside the critical organizational considerations and success factors required to maximize their impact on the speed, efficiency, and probability of success.

stat.OT

FrankenStat I: a New Approach to Pulsar Timing Array Data Combination

In 2023, after more than two decades of searching, pulsar timing array (PTA) collaborations around the world announced evidence for a stochastic gravitational wave background. It was quickly followed by work from the International Pulsar Timing Array (IPTA), demonstrating that the results of regional collaborations were consistent with each other. The combination of these datasets is still ongoing and represents a significant investment of time and expertise. In that IPTA comparison, authors of this letter combined the separate datasets in the standard PTA optimal detection statistic for cross-correlations incoherently, that is, the data was combined without fitting a merged timing model across all PTA datasets, treating datasets of the same pulsar as independent, and neglecting the "same pulsar, different datasets" cross-correlations. This work refines that method by extending its core ideas beyond detection statistics and into a full, general data-combination method. We have demonstrated its efficacy and extreme efficiency on simulated data. This new method, \textit{FrankenStat}, is very similar in sensitivity and parameter-constraining power to traditional data combination methods while completing the full data combination in just a few minutes.

astro-ph.CO

The Estimand Framework and Causal Inference: Complementary not Competing Paradigms

The creation of the ICH E9 (R1) estimands framework has led to more precise specification of the treatment effects of interest in the design and statistical analysis of clinical trials. However, it is unclear how the new framework relates to causal inference, as both approaches appear to define what is being estimated and have a quantity labelled an estimand. Using illustrative examples, we show that both approaches can be used to define a population-based summary of an effect on an outcome for a specified population and highlight the similarities and differences between these approaches. We demonstrate that the ICH E9 (R1) estimand framework offers a descriptive, structured approach that is more accessible to non-mathematicians, facilitating clearer communication of trial objectives and results. We then contrast this with the causal inference framework, which provides a mathematically precise definition of an estimand, and allows the explicit articulation of assumptions through tools such as causal graphs. Despite these differences, the two paradigms should be viewed as complementary rather than competing. The combined use of both approaches enhances the ability to communicate what is being estimated. We encourage those familiar with one framework to appreciate the concepts of the other to strengthen the robustness and clarity of clinical trial design, analysis, and interpretation.

stat.ME

The NANOGrav 15 yr Data Set: Harmonic Analysis of the Pulsar Angular Correlations

Pulsar timing array observations have found evidence for an isotropic gravitational wave background with the Hellings-Downs angular correlations, expected from general relativity. This interpretation hinges on the measured shape of the angular correlations, which is predominately quadrupolar under general relativity. Here we explore a more flexible parameterization: we expand the angular correlations into a sum of Legendre polynomials and use a Bayesian analysis to constrain their coefficients with the 15-year pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). When including Legendre polynomials with multipoles $\ell \geq 2$, we only find a significant signal in the quadrupole with an amplitude consistent with general relativity and non-zero at the $\sim 95\%$ confidence level and a Bayes factor of 200. When we include multipoles $\ell \leq 1$, the Bayes factor evidence for quadrupole correlations decreases by more than an order of magnitude due to evidence for a monopolar signal at approximately 4 nHz which has also been noted in previous analyses of the NANOGrav 15-year data. Further work needs to be done in order to better characterize the properties of this monopolar signal and its effect on the evidence for quadrupolar angular correlations.

astro-ph.HE

Deep Neural Emulation of the Supermassive Black-hole Binary Population

While supermassive black-hole (SMBH)-binaries are not the only viable source for the low-frequency gravitational wave background (GWB) signal evidenced by the most recent pulsar timing array (PTA) data sets, they are expected to be the most likely. Thus, connecting the measured PTA GWB spectrum and the underlying physics governing the demographics and dynamics of SMBH-binaries is extremely important. Previously, Gaussian processes (GPs) and dense neural networks have been used to make such a connection by being built as conditional emulators; their input is some selected evolution or environmental SMBH-binary parameters and their output is the emulated mean and standard deviation of the GWB strain ensemble distribution over many Universes. In this paper, we use a normalizing flow (NF) emulator that is trained on the entirety of the GWB strain ensemble distribution, rather than only mean and standard deviation. As a result, we can predict strain distributions that mirror underlying simulations very closely while also capturing frequency covariances in the strain distributions as well as statistical complexities such as tails, non-Gaussianities, and multimodalities that are otherwise not learnable by existing techniques. In particular, we feature various comparisons between the NF-based emulator and the GP approach used extensively in past efforts. Our analyses conclude that the NF-based emulator not only outperforms GPs in the ease and computational cost of training but also outperforms in the fidelity of the emulated GWB strain ensemble distributions.

astro-ph.IM

CMB and energy conservation limits on nanohertz gravitational waves

The recent evidence for a stochastic gravitational wave background (GWB) in the nanohertz band, announced by pulsar timing array (PTA) collaborations around the world, has been posited to be sourced by either a population of supermassive black holes binaries or perturbations of spacetime near the inflationary era, generated by a zoo of various new physical phenomena. Gravitational waves (GWs) from these latter models would be explained by extensions to the standard model of cosmology and possibly to the standard model of particle physics. While PTA datasets can be used to characterize the parameter spaces of these models, energy conservation and limits from the cosmic microwave background (CMB) can be used $\textit{a priori}$ to bound those parameter spaces. Here we demonstrate that taking a simple rule for energy conservation and using CMB bounds on the radiation energy density can set stringent limits on the parameters for these models.

gr-qc

The NANOGrav 15 yr Data Set: Looking for Signs of Discreteness in the Gravitational-wave Background

The cosmic merger history of supermassive black hole binaries (SMBHBs) is expected to produce a low-frequency gravitational wave background (GWB). Here we investigate how signs of the discrete nature of this GWB can manifest in pulsar timing arrays through excursions from, and breaks in, the expected $f_{\mathrm{GW}}^{-2/3}$ power-law of the GWB strain spectrum. To do this, we create a semi-analytic SMBHB population model, fit to NANOGrav's 15 yr GWB amplitude, and with 1,000 realizations we study the populations' characteristic strain and residual spectra. Comparing our models to the NANOGrav 15 yr spectrum, we find two interesting excursions from the power-law. The first, at $2 \; \mathrm{nHz}$, is below our GWB realizations with $p$-value significance $p = 0.05$ to $0.06$ ($\approx 1.8 \sigma - 1.9 \sigma$). The second, at $16 \; \mathrm{nHz}$, is above our GWB realizations with $p = 0.04$ to $0.15$ ($\approx 1.4 \sigma - 2.1 \sigma$). We explore the properties of a loud SMBHB which could cause such an excursion. Our simulations also show that the expected number of SMBHBs decreases by three orders of magnitude, from $\sim 10^6$ to $\sim 10^3$, between $2\; \mathrm{nHz}$ and $20 \; \mathrm{nHz}$. This causes a break in the strain spectrum as the stochasticity of the background breaks down at $26^{+28}_{-19} \; \mathrm{nHz}$, consistent with predictions pre-dating GWB measurements. The diminished GWB signal from SMBHBs at frequencies above the $26~\mathrm{nHz}$ break opens a window for PTAs to detect continuous GWs from individual SMBHBs or GWs from the early universe.

astro-ph.HE

Estimation methods for estimands using the treatment policy strategy; a simulation study based on the PIONEER 1 Trial

Estimands using the treatment policy strategy for addressing intercurrent events are common in Phase III clinical trials. One estimation approach for this strategy is retrieved dropout whereby observed data following an intercurrent event are used to multiply impute missing data. However, such methods have had issues with variance inflation and model fitting due to data sparsity. This paper introduces likelihood-based versions of these approaches, investigating and comparing their statistical properties to the existing retrieved dropout approaches, simpler analysis models and reference-based multiple imputation. We use a simulation based upon the data from the PIONEER 1 Phase III clinical trial in Type II diabetics to present complex and relevant estimation challenges. The likelihood-based methods display similar statistical properties to their multiple imputation equivalents, but all retrieved dropout approaches suffer from high variance. Retrieved dropout approaches appear less biased than reference-based approaches, resulting in a bias-variance trade-off, but we conclude that the large degree of variance inflation is often more problematic than the bias. Therefore, only the simpler retrieved dropout models appear appropriate as a primary analysis in a clinical trial, and only where it is believed most data following intercurrent events will be observed. The jump-to-reference approach may represent a more promising estimation approach for symptomatic treatments due to its relatively high power and ability to fit in the presence of much missing data, despite its strong assumptions and tendency towards conservative bias. More research is needed to further develop how to estimate the treatment effect for a treatment policy strategy.

stat.AP

Estimating hypothetical estimands with causal inference and missing data estimators in a diabetes trial

The recently published ICH E9 addendum on estimands in clinical trials provides a framework for precisely defining the treatment effect that is to be estimated, but says little about estimation methods. Here we report analyses of a clinical trial in type 2 diabetes, targeting the effects of randomised treatment, handling rescue treatment and discontinuation of randomised treatment using the so-called hypothetical strategy. We show how this can be estimated using mixed models for repeated measures, multiple imputation, inverse probability of treatment weighting, G-formula and G-estimation. We describe their assumptions and practical details of their implementation using packages in R. We report the results of these analyses, broadly finding similar estimates and standard errors across the estimators. We discuss various considerations relevant when choosing an estimation approach, including computational time, how to handle missing data, whether to include post intercurrent event data in the analysis, whether and how to adjust for additional time-varying confounders, and whether and how to model different types of ICE separately.

stat.AP

PTArcade

This is a lightweight manual for PTArcade, a wrapper of ENTERPRISE and ceffyl that allows for easy implementation of new-physics searches in PTA data. In this manual, we describe how to get PTArcade installed (either on your local machine or an HPC cluster). We discuss how to define a stochastic or deterministic signal and how PTArcade implements these signals in PTA-analysis pipelines. Finally, we show how to handle and analyze the PTArcade output using a series of utility functions that come together with PTArcade.

hep-ph

Hypersonic Weapons-Part 1: Background and Vulnerability to Missile Defenses

Assessing the desirability of hypersonic glide vehicles (HGVs) requires understanding what capabilities they may provide compared to alternative systems that could carry out the same missions, particularly given the technical difficulties and additional costs of developing hypersonic gliders compared to more established technologies. Part 1 of this paper considers the primary motivations given for developing HGVs and summarizes the current development programs of the United States, Russia, and China. It then analyzes the vulnerability of hypersonic boost-glide vehicles (BGVs) to missile defenses and finds that evading the most capable current endo-atmospheric defenses requires that BGVs maintain speeds significantly higher than Mach 5 throughout their glide phase. Achieving these high speeds has important implications for the mass and range of these weapons, which in turn affect what delivery vehicles can carry them and how their performance compares to other means of delivery, as is discussed in Part 2.

physics.soc-ph

Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic

The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

q-bio.OT

Improved SAR Imaging Via Cross-Learning from Camera Images

In this paper, we propose a novel concept of cross-learning, in order to improve SAR images by learning from the camera images. We use a multi-level abstraction approach to materialise knowledge transfer between the two modalities. We also compare the performance of other possible approaches. We provide experimental results on real data to validate the proposed concept.

eess.SP

Parallel convolution processing using an integrated photonic tensor core

With the proliferation of ultra-high-speed mobile networks and internet-connected devices, along with the rise of artificial intelligence, the world is generating exponentially increasing amounts of data - data that needs to be processed in a fast, efficient and smart way. These developments are pushing the limits of existing computing paradigms, and highly parallelized, fast and scalable hardware concepts are becoming progressively more important. Here, we demonstrate a computational specific integrated photonic tensor core - the optical analog of an ASIC-capable of operating at Tera-Multiply-Accumulate per second (TMAC/s) speeds. The photonic core achieves parallelized photonic in-memory computing using phase-change memory arrays and photonic chip-based optical frequency combs (soliton microcombs). The computation is reduced to measuring the optical transmission of reconfigurable and non-resonant passive components and can operate at a bandwidth exceeding 14 GHz, limited only by the speed of the modulators and photodetectors. Given recent advances in hybrid integration of soliton microcombs at microwave line rates, ultra-low loss silicon nitride waveguides, and high speed on-chip detectors and modulators, our approach provides a path towards full CMOS wafer-scale integration of the photonic tensor core. While we focus on convolution processing, more generally our results indicate the major potential of integrated photonics for parallel, fast, and efficient computational hardware in demanding AI applications such as autonomous driving, live video processing, and next generation cloud computing services.

physics.optics