arXiv subjects

Patrick Owen

Publications and source records attributed to Patrick Owen.

15 recordsLinked to original sources

arXiv2026

RAISE: LLM-based Automated Heuristic Design with Robust Adversary Instance Search

Automated Heuristic Design (AHD) with Large Language Models (LLMs) has shown remarkable progress in discovering high-quality heuristics. However, existing LLM-based AHD methods optimize heuristics for a fixed training instance set and may fail catastrophically when deployed under real-world distributional shifts. We propose Robust Adversary Instance Search (RAISE), a framework that integrates constrained worst-case instance search within a principled neighborhood of the training distribution into the LLM-based evolutionary search loop. RAISE treats robust AHD as a constrained adversarial instance search problem: the outer loop evolves heuristics via LLM operators, while an LLM-free inner loop efficiently identifies hard instances within an epsilon-ball around the training instance set using a basis distribution parameterization with boundary projection. Comprehensive experiments on Online Bin Packing (OBP), Online Job Shop Scheduling (OJSP), and Online Vehicle Routing (OVRP) across five distribution families demonstrate that existing LLM-based AHD methods degrade by up to 19 times under distribution shift, while RAISE consistently maintains strong performance across all tested distributions and problem scales

cs.AI↗

arXiv2026

Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation

Target trial emulation (TTE) enables causal questions to be studied with observational data when randomized controlled trials (RCTs) are infeasible. Yet treatment-effect methods often address causal estimation, missingness, and temporal structure separately, limiting their robustness in electronic health records (EHRs), where time-varying confounding and missing-not-at-random (MNAR) biomarkers can reach 50%--80%. We propose a two-stage pipeline for treatment effect estimation from incomplete longitudinal EHRs. First, CausalFlow-T, a directed acyclic graph (DAG)-constrained normalizing flow with long short-term memory (LSTM)-encoded patient history, performs exact invertible counterfactual inference, avoiding approximation errors from variational inference and separating confounding through explicit causal structure. Ablations on four synthetic and one semi-synthetic benchmark with known counterfactuals show that DAG constraints and exact inference address distinct failure modes: neither compensates for the other. Second, because CausalFlow-T requires completed inputs, we introduce an LLM-driven evolutionary imputer that proposes executable imputation operators rather than individual entries, and evaluate it with three large language model (LLM) backends, including two open-source models. Across 30%--80% MNAR missingness, this imputer achieves the best pooled rank over biomarker and causal metrics, leading in point-wise accuracy and temporal extrapolation while preserving average treatment effect (ATE) recovery as statistical baselines degrade. On Swiss primary-care EHRs from adults with type 2 diabetes initiating a GLP-1 receptor agonist or SGLT-2 inhibitor, the pipeline estimates a per-protocol weight-loss difference of -0.98 kg [95% CI -1.01, -0.96] favoring GLP-1 receptor agonists, consistent with randomized evidence and obtained from realistically incomplete real-world EHRs.

cs.LG↗

arXiv2026

Large Language Models for Physics Instrument Design

We study the use of large language models (LLMs) for physics instrument design and compare their performance to reinforcement learning (RL). Using only prompting, LLMs are given task constraints and summaries of prior high-scoring designs and propose complete detector configurations, which we evaluate with the same simulators and reward functions used in RL-based optimization. Although RL yields stronger final designs, we find that modern LLMs consistently generate valid, resource-aware, and physically meaningful configurations that draw on broad pretrained knowledge of detector design principles and particle--matter interactions, despite having no task-specific training. Based on this result, as a first step toward hybrid design workflows, we explore pairing the LLMs with a dedicated trust region optimizer, serving as a precursor to future pipelines in which LLMs propose and structure design hypotheses while RL performs reward-driven optimization. Based on these experiments, we argue that LLMs are well suited as meta-planners: they can design and orchestrate RL-based optimization studies, define search strategies, and coordinate multiple interacting components within a unified workflow. In doing so, they point toward automated, closed-loop instrument design in which much of the human effort required to structure and supervise optimization can be reduced.

physics.ins-det↗

arXiv2025

Towards replacing detector simulation with heterogeneous GNNs in flavour physics analyses

Driven by the increasing volume of recorded data, the demand for simulation from experiments based at the Large Hadron Collider will rise sharply in the coming years. Addressing this demand solely with existing computationally intensive workflows is not feasible. This paper introduces a new fast simulation tool designed to address this demand at the LHCb experiment. This tool emulates the detector response to arbitrary multibody decay topologies at LHCb. Rather than memorising specific decay channels, the model learns generalisable patterns within the response, allowing it to interpolate to channels not present in the training data. Novel heterogeneous graph neural network architectures are employed that are designed to embed the physical characteristics of the task directly into the network structure. We demonstrate the performance of the tool across a range of decay topologies, showing the networks can correctly model the relationships between complex variables. The architectures and methods presented are generic and could readily be adapted to emulate workflows at other simulation-intensive particle physics experiments.

hep-ex↗

arXiv2024

Physics Instrument Design with Reinforcement Learning

We present a case for the use of Reinforcement Learning (RL) for the design of physics instrument as an alternative to gradient-based instrument-optimization methods. It's applicability is demonstrated using two empirical studies. One is longitudinal segmentation of calorimeters and the second is both transverse segmentation as well longitudinal placement of trackers in a spectrometer. Based on these experiments, we propose an alternative approach that offers unique advantages over differentiable programming and surrogate-based differentiable design optimization methods. First, Reinforcement Learning (RL) algorithms possess inherent exploratory capabilities, which help mitigate the risk of convergence to local optima. Second, this approach eliminates the necessity of constraining the design to a predefined detector model with fixed parameters. Instead, it allows for the flexible placement of a variable number of detector components and facilitates discrete decision-making. We then discuss the road map of how this idea can be extended into designing very complex instruments. The presented study sets the stage for a novel framework in physics instrument design, offering a scalable and efficient framework that can be pivotal for future projects such as the Future Circular Collider (FCC), where most optimized detectors are essential for exploring physics at unprecedented energy scales.

physics.ins-det↗

arXiv2023

FunTuple: A new N-tuple component for offline data processing at the LHCb experiment

The offline software framework of the LHCb experiment has undergone a significant overhaul to tackle the data processing challenges that will arise in the upcoming Run 3 and Run 4 of the Large Hadron Collider. This paper introduces FunTuple, a novel component developed for offline data processing within the LHCb experiment. This component enables the computation and storage of a diverse range of observables for both reconstructed and simulated events by leveraging on the tools initially developed for the trigger system. This feature is crucial for ensuring consistency between trigger-computed and offline-analysed observables. The component and its tool suite offer users flexibility to customise stored observables, and its reliability is validated through a full-coverage set of rigorous unit tests. This paper comprehensively explores FunTuple's design, interface, interaction with other algorithms, and its role in facilitating offline data processing for the LHCb experiment for the next decade and beyond.

physics.data-an↗

arXiv2023

The DL Advocate: Playing the devil's advocate with hidden systematic uncertainties

We propose a new method based on machine learning to \emph{play the devil's advocate} and investigate the impact of unknown systematic effects in a quantitative way. This method proceeds by reversing the measurement process and using the physics results to interpret systematic effects under the Standard Model hypothesis. We explore this idea with two alternative approaches: the first one relies on a combination of gradient descent and optimisation techniques, its application and potentiality is illustrated with an example that studies the branching fraction measurement of a heavy-flavour decay. The second method employs reinforcement learning and it is applied to the determination of the $P_{5}^{'}$ angular observable in $B^0 \to K^{*0} \mu^+\mu^-$ decays. We find that for the former, the size of a hypothetical hidden systematic uncertainty strongly depends on the kinematic overlap between the signal and normalisation channel, while the latter is very robust against possible mismodellings of the efficiency.

hep-ex↗

arXiv2021

A general effective field theory description of $b \to s l^+ l^-$ lepton universality ratios

We construct an expression for a general lepton flavour universality (LFU) ratio, $R_{X}$, in $b\to s l^+ l^-$ decays in terms of a series of hadronic quantities which can be treated as nuisance parameters. This expression allows to include any LFU ratio in global fits of $b\to s l^+ l^-$ short-distance parameters, even in the absence of a precise knowledge of the corresponding hadronic structure. The absence of sizeable LFU violation and the approximate left-handed structure of the Standard Model amplitude imply that only a very limited set of hadronic parameters hamper the sensitivity of $R_X$ to a possible LFU violation of short-distance origin. A global $b\to s l^+ l^-$ combination is performed including the measurement of $R_{pK}$ for the first time, resulting in a significance of new physics of $4.2\,σ$. In light of this, we evaluate the impact on the global significance of new physics using a set of experimentally promising non-exclusive $R_X$ measurements that LHCb can perform, and find that they can significantly increase the discovery potential of the experiment.

hep-ph↗

arXiv2021

On the significance of new physics in $b\to s\ell^+\ell^-$ decays

Motivated by deviations with respect to Standard Model predictions in $b\to s\ell^+\ell^-$ decays, we evaluate the global significance of the new physics hypothesis in this system by including the {\it look-elsewhere effect} for the first time. We estimate the trial-factor with pseudo-experiments and find that it can be as large as seven. We calculate the global significance for the new physics hypothesis by considering the most general description of a non-standard $b\to s\ell^+\ell^-$ amplitude of short-distance origin. Theoretical uncertainties are treated in a highly conservative way by absorbing the corresponding effects into a redefinition of the Standard Model amplitude. Using the most recent measurements of LHCb, ATLAS and CMS, we obtain the global significance to be $4.3$ standard deviations.

hep-ph↗

arXiv2021

Isospin extrapolation as a method to study inclusive $\bar{B} \to X_{s} \ell^{+}\ell^{-}$ decays

A novel approach to reconstruct inclusive $\bar{B} \to X_{s} \ell^{+}\ell^{-}$ decays is presented. The method relies on isopsin symmetry to extrapolate the semi-inclusive signature $X_{b}\to K^{+} \ell^{+}\ell^{-} X$ to the fully inclusive rate in $B^{+}$ and $B^{0}$ decays. We investigate the possibility to measure branching fractions and other observables such as lepton universality ratios and $CP$ asymmetries. As a proof of concept, fast simulation is used to compare the $X_{b}\to K^{+} \ell^{+}\ell^{-} X$ signature with a fully inclusive approach. Several experimental advantages are seen which have the potential to make measurements of inclusive $\bar{B} \to X_{s} \ell^{+}\ell^{-}$ decays tractable at a hadron collider.

hep-ph↗

arXiv2020

Hunting for $B^+\to K^+ τ^+τ^-$ imprints on the $B^+ \to K^+ μ^+μ^-$ dimuon spectrum

We investigate the possibility of indirectly constraining the $B^{+}\to K^{+}τ^+τ^-$ decay rate using precise data on the $B^{+}\to K^{+}μ^+μ^-$ dimuon spectrum. To this end, we estimate the distortion of the spectrum induced by the $B^{+}\to K^{+}τ^+τ^-\to K^{+} μ^+μ^-$ re-scattering process, and propose a method to simultaneously constrain this (non-standard) contribution and the long-distance effects associated to hadronic intermediate states. The latter are constrained using the analytic properties of the amplitude combined with data and perturbative calculations. Finally, we estimate the sensitivity expected at the LHCb experiment with present and future datasets. We find that constraints on the branching fraction of $O(10^{-3})$, competitive with current direct bounds, can be achieved with the current dataset, while bounds of $O(10^{-4})$ could be obtained with the LHCb upgrade-II luminosity.

hep-ph↗

arXiv2020

Probing effects of new physics in $Λ^0_{b}\toΛ^+_{c}μ^{-}\barν_μ$ decays

We present, for the first time, the six-fold differential decay density expression for $Λ^0_b\toΛ^+_{c} l^- \barν_{l}$, taking into account the polarisation of the $Λ^0_b$ baryon and a complete basis of new physics operators. Using the expected yield in the current dataset collected at the LHCb experiment, we present sensitivity studies to determine the experimental precision on the Wilson coefficients of the new physics operators with $Λ^0_{b}\toΛ^+_{c}μ^{-}\barν_μ$ decays in two scenarios. In the first case, unpolarised $Λ^0_{b}\toΛ^+_{c}μ^{-}\barν_μ$ decays with $Λ^+_c\to p K^+ π^-$ are considered, whereas polarised $Λ^0_{b}\toΛ^+_{c}μ^{-}\barν_μ$ decays with $Λ^+_c \to p K^0_S$ are studied in the second. For the latter scenario, the experimental precision that can be achieved on the determination of $Λ^0_b$ polarisation and $Λ^+_c$ weak decay asymmetry parameter is also presented.

hep-ph↗

arXiv2019

Summary of the 2018 CKM working group on semileptonic and leptonic $b$-hadron decays

A summary of WG II of the CKM 2018 conference on semileptonic and leptonic $b$-hadron decays is presented. This includes discussions on the CKM matrix element magitudes $|V_{ub}|$ and $|V_{cb}|$, lepton universality tests such as $R(D^{*})$ and leptonic decays. As is usual for semileptonic and leptonic decays, much discussion is devoted towards the interplay between theoretical QCD calculations and the experimental measurements.

hep-ex↗

arXiv2018

Testing lepton flavour universality in semileptonic $Λ_b \to Λ_c^*$ decays

Lepton Flavour Universality tests with semileptonic $Λ_b\toΛ_c^*$ decays are important to corroborate the present anomalies in the similar ratios $R_{D^{(*)}}$, and can provide complementary constraints on possible origins of these anomalies beyond the Standard Model. In this paper we provide - for the first time - all the necessary theoretical ingredients to perform and interpret measurements of $R_{Λ_c^*}$ at the LHCb experiment. For this, we revisit the heavy-quark expansion of the relevant hadronic matrix elements, and provide their expressions to order $α_s$ and $1/m$ accuracy. Moreover, we study the sensitivity to the form factor parameters given the projected size and purity of upcoming and future LHCb datasets of $Λ_b\to Λ_c^*μ\barν$ decays. We demonstrate explicitly the need to perform a simultaneous fit to both $Λ_c^*$ final states. Finally, we provide projections for the uncertainty of $R_{Λ_c^*}$ based on the form factor analysis from semimuonic decays and theoretical relations based on the heavy-quark expansion.

hep-ph↗

arXiv2018

An empirical model of the long-distance contributions to $\bar{B}^{0} \rightarrow \bar{K}^{*0}μ^{+}μ^{-}$ transitions

A method for analysing the hadronic resonance contributions in $\bar{B}^{0} \rightarrow \bar{K}^{*0}μ^{+}μ^{-}$ decays is presented. This method uses an empirical model that relies on measurements of the branching fractions and polarisation amplitudes of final states involving $J^{PC}=1^{--}$ resonances, relative to the short-distance component, across the full dimuon mass spectrum of $\bar{B}^{0} \rightarrow \bar{K}^{*0}μ^{+}μ^{-}$ transitions. The model is in good agreement with existing calculations of hadronic non-local effects. The effect of this contribution to the angular observables is presented and it is demonstrated how the narrow resonances in the $q^{2}$ spectrum provide a dramatic enhancement to $CP$-violating effects in the short-distance amplitude. Finally, a study of the hadronic resonance effects on lepton universality ratios, $R_{K^{(*)}}$, in the presence of new physics is presented.

hep-ph↗