arXiv subjects

James Whitehead

Publications and source records attributed to James Whitehead.

16 recordsLinked to original sources

arXiv2026

PDF evolution in alternative factorisation schemes

Beyond leading order, parton distribution functions (PDFs) require a choice of factorisation scheme to be defined unambiguously. Different choices of factorisation scheme lead to PDFs that satisfy modified DGLAP evolution equations, relative to the conventional $\overline{\mathrm{MS}}$ scheme. In this paper we derive the NLO DGLAP splitting functions for PDFs in alternative factorisation schemes, including for a parametrised scheme spanning a subspace of the general factorisation-scheme space. We plot their Mellin-space counterparts, the anomalous dimensions, and study the leading large- and small-$x$ behaviour, relevant to resummation. We find that the leading behaviour admits a natural interpretation as a modified effective evolution scale. This is an essential step towards being able to evolve and fit PDFs in alternative schemes for use within QCD calculations.

hep-ph↗

arXiv2025

KrkNLO matching and phenomenology for vector boson processes

The combination of NLO matrix elements with parton showers is indispensable for LHC physics. Differences between matching methods introduce matching uncertainties, corresponding to formally higher-order terms. We recently presented the process-independent generalisation of the KrkNLO method for NLO matching, which employs a modified PDF factorisation scheme to achieve NLO accuracy. With this factorisation scheme, the method can be used for colour-singlet final-states, and was previously implemented in the Herwig Monte Carlo Event Generator and applied to the diphoton-production process. Here we present the extension of the implementation of the KrkNLO method within Herwig to support the full class of applicable processes, using an external matrix-element library. We re-validate the implementation, and use it to study the NLO matching uncertainty for four vector-boson production processes at the LHC: $W$, $Z\gamma$, $WW$ and $ZZ$. We demonstrate that the KrkNLO method effectively eliminates the negative-weight problem in NLO event generation, across the four processes studied. We provide detailed comparisons between KrkNLO and variants of the MC@NLO method with different shower starting-scale choices, across processes and throughout phase-space, including double-differential observables. For each process, we compare the predictions to LHC data from ATLAS.

hep-ph↗

arXiv2025

Flavoured jet algorithms: a comparative study

The accurate identification of heavy-flavour jets, those which originate from bottom or charm quarks, is crucial for precision studies of the Standard Model and searches for new physics. However, assigning flavour to jets presents significant challenges, primarily due to issues with infrared and collinear (IRC) safety. This paper aims to address these challenges by evaluating recently-proposed jet algorithms designed to be IRC-safe and applicable in high-precision measurements. We compare these algorithms across benchmark heavy-flavour production processes and kinematic regimes that are relevant for LHC phenomenology. Exploiting both fixed-order calculations in QCD as well as parton shower simulations, we analyse the infrared sensitivity of these new algorithms at different stages of the event evolution and compare to flavour-labelling strategies currently adopted by LHC collaborations. The results highlight that, while all algorithms lead to more robust flavour-assignments compared to current techniques, they vary in performance depending on the observable and energy regime. The study lays groundwork for robust, flavour-aware jet analyses in current and future collider experiments to maximise the physics potential of experimental data by reducing discrepancies between theoretical and experimental methods.

hep-ph↗

arXiv2025

Factorisation schemes for proton PDFs

Beyond leading-order, perturbative QCD requires a choice of factorisation scheme to define the parton distribution functions (PDFs) and hard-process cross-section. The modified minimal-subtraction ($\overline{\mathrm{MS}}$) scheme has long been adopted as the default choice due to its simplicity. Alternative schemes have been proposed with specific purposes, including, recently, PDF positivity and NLO parton-shower matching. In this paper we assemble these schemes in a common notation for the first time. We perform a detailed comparison of their features, both analytically and numerically, and estimate the resulting factorisation-scheme uncertainty for LHC phenomenology.

hep-ph↗

arXiv2024

KrkNLO matching for colour-singlet processes

Matched calculations combining perturbative QCD with parton showers are an indispensable tool for LHC physics. Two methods for NLO matching are in widespread use: MC@NLO and POWHEG. We describe an alternative, KrkNLO, reformulated to be easily applicable to any colour-singlet process. The primary distinguishing characteristic of KrkNLO is its use of an alternative factorisation scheme, the 'Krk' scheme, to achieve NLO accuracy. We describe the general implementation of KrkNLO in Herwig 7, using diphoton production as a test process. We systematically compare its predictions to those produced by MC@NLO with several different choices of shower scale, both truncated to one-emission and with the shower running to completion, and to ATLAS data from LHC Run 2.

hep-ph↗

arXiv2023

Herwig 7.3 Release Note

A new release of the Monte Carlo event generator Herwig (version 7.3) has been launched. This iteration encompasses several enhancements over its predecessor, version 7.2. Noteworthy upgrades include: the implementation of a process-independent electroweak angular-ordered parton shower integrated with QCD and QED radiation; a new recoil scheme for initial-state radiation improving the behaviour of the angular-ordered parton shower; the incorporation of the heavy quark effective theory to refine the hadronization and decay of excited heavy mesons and heavy baryons; a dynamic strategy to regulate the kinematic threshold of cluster splittings within the cluster hadronization model; several improvements to the structure of the cluster hadronization model allowing for refined models; the possibility to extract event-by-event hadronization corrections in a well-defined way; the possibility of using the string model, with a dedicated tune. Additionally, a new tuning of the parton shower and hadronization parameters has been executed. This article discusses the novel features introduced in version 7.3.0.

hep-ph↗

arXiv2023

Spatially Varying Nanophotonic Neural Networks

The explosive growth of computation and energy cost of artificial intelligence has spurred strong interests in new computing modalities as potential alternatives to conventional electronic processors. Photonic processors that execute operations using photons instead of electrons, have promised to enable optical neural networks with ultra-low latency and power consumption. However, existing optical neural networks, limited by the underlying network designs, have achieved image recognition accuracy far below that of state-of-the-art electronic neural networks. In this work, we close this gap by embedding massively parallelized optical computation into flat camera optics that perform neural network computation during the capture, before recording an image on the sensor. Specifically, we harness large kernels and propose a large-kernel spatially-varying convolutional neural network learned via low-dimensional reparameterization techniques. We experimentally instantiate the network with a flat meta-optical system that encompasses an array of nanophotonic structures designed to induce angle-dependent responses. Combined with an extremely lightweight electronic backend with approximately 2K parameters we demonstrate a reconfigurable nanophotonic neural network reaches 72.76\% blind test classification accuracy on CIFAR-10 dataset, and, as such, the first time, an optical neural network outperforms the first modern digital neural network -- AlexNet (72.64\%) with 57M parameters, bringing optical neural network into modern deep learning era.

cs.CV↗

arXiv2021

Neural Nano-Optics for High-quality Thin Lens Imaging

Nano-optic imagers that modulate light at sub-wavelength scales could unlock unprecedented applications in diverse domains ranging from robotics to medicine. Although metasurface optics offer a path to such ultra-small imagers, existing methods have achieved image quality far worse than bulky refractive alternatives, fundamentally limited by aberrations at large apertures and low f-numbers. In this work, we close this performance gap by presenting the first neural nano-optics. We devise a fully differentiable learning method that learns a metasurface physical structure in conjunction with a novel, neural feature-based image reconstruction algorithm. Experimentally validating the proposed method, we achieve an order of magnitude lower reconstruction error. As such, we present the first high-quality, nano-optic imager that combines the widest field of view for full-color metasurface operation while simultaneously achieving the largest demonstrated 0.5 mm, f/2 aperture.

physics.optics↗

arXiv2021

Free-space optical neural network based on thermal atomic nonlinearity

As artificial neural networks (ANNs) continue to make strides in wide-ranging and diverse fields of technology, the search for more efficient hardware implementations beyond conventional electronics is gaining traction. In particular, optical implementations potentially offer extraordinary gains in terms of speed and reduced energy consumption due to intrinsic parallelism of free-space optics. At the same time, a physical nonlinearity, a crucial ingredient of an ANN, is not easy to realize in free-space optics, which restricts the potential of this platform. This problem is further exacerbated by the need to perform the nonlinear activation also in parallel for each data point to preserve the benefit of linear free-space optics. Here, we present a free-space optical ANN with diffraction-based linear weight summation and nonlinear activation enabled by the saturable absorption of thermal atoms. We demonstrate, via both simulation and experiment, image classification of handwritten digits using only a single layer and observed 6-percent improvement in classification accuracy due to the optical nonlinearity compared to a linear model. Our platform preserves the massive parallelism of free-space optics even with physical nonlinearity, and thus opens the way for novel designs and wider deployment of optical ANNs.

cs.ET↗

arXiv2021

Non-volatile reconfigurable integrated photonics enabled by broadband low-loss phase change material

Phase change materials (PCMs) have long been used as a storage medium in rewritable compact disk and later in random access memory. In recent years, the integration of PCMs with nanophotonic structures has introduced a new paradigm for non-volatile reconfigurable optics. However, the high loss of the archetypal PCM Ge2Sb2Te5 in both visible and telecommunication wavelengths has fundamentally limited its applications. Sb2S3 has recently emerged as a wide-bandgap PCM with transparency windows ranging from 610nm to near-IR. In this paper, the strong optical phase modulation and low optical loss of Sb2S3 are experimentally demonstrated for the first time in integrated photonic platforms at both 750nm and 1550nm. As opposed to silicon, the thermo-optic coefficient of Sb2S3 is shown to be negative, making the Sb2S3-Si hybrid platform less sensitive to thermal fluctuation. Finally, a Sb2S3 integrated non-volatile microring switch is demonstrated which can be tuned electrically between a high and low transmission state with a contrast over 30dB. Our work experimentally verified the prominent phase modification and low loss of Sb2S3 in wavelength ranges relevant for both solid-state quantum emitter and telecommunication, enabling potential applications such as optical field programmable gate array, post-fabrication trimming, and large-scale integrated quantum photonic network.

physics.optics↗

arXiv2020

Scale and isolation sensitivity of diphoton distributions at the LHC

Precision measurements of diphoton distributions at the LHC display some tension with theory predictions, obtained at next-to-next-to-leading order (NNLO) in QCD. We revisit the theoretical uncertainties arising from the approximation of the experimental photon isolation by smooth-cone isolation, and from the choice of functional form for the renormalisation and factorisation scales. We find that the resulting variations are substantial overall, and enhanced in certain regions. We discuss the infrared sensitivity at the cone boundaries in cone-based isolation in related distributions. Finally, we compare predictions made with alternative choices of dynamical scale and isolation prescriptions to experimental data from ATLAS at 8 TeV, observing improved agreement. This contrasts with previous results, highlighting that scale choice and isolation prescription are potential sources of theoretical uncertainty that were previously underestimated.

hep-ph↗

arXiv2020

Dispersive coupling between MoSe2 and a zero-dimensional integrated nanocavity

Establishing a coherent interaction between a material resonance and an optical cavity is a necessary first step for the development of semiconductor quantum optics. Here we demonstrate a coherent interaction between the neutral exciton in monolayer MoSe2 and a zero-dimensional, small mode volume nanocavity. This is observed through a dispersive shift of the cavity resonance when the exciton-cavity detuning is decreased, with an estimated exciton-cavity coupling of ~4.3 meV and a cooperativity of C~3.4 at 80 Kelvin. This coupled exciton-cavity platform is expected to reach the strong light-matter coupling regime (i.e., with C~380) at 4 Kelvin for applications in quantum or ultra-low power nanophotonics.

physics.optics↗

arXiv2020

Metasurface Integrated Monolayer Exciton Polariton

Monolayer transition metal dichalcogenides (TMDs) are the first truly two-dimensional (2D) semiconductor, providing an excellent platform to investigate light-matter interaction in the 2D limit. Apart from fundamental scientific exploration, this material system has attracted active research interest in the nanophotonic devices community for its unique optoelectronic properties. The inherently strong excitonic response in monolayer TMDs can be further enhanced by exploiting the temporal confinement of light in nanophotonic structures. Dielectric metasurfaces are one such two-dimensional nanophotonic structures, which have recently demonstrated strong potential to not only miniaturize existing optical components, but also to create completely new class of designer optics. Going beyond passive optical elements, researchers are now exploring active metasurfaces using emerging materials and the utility of metasurfaces to enhance the light-matter interaction. Here, we demonstrate a 2D exciton-polariton system by strongly coupling atomically thin tungsten diselenide (WSe2) monolayer to a silicon nitride (SiN) metasurface. Via energy-momentum spectroscopy of the WSe2-metasurface system, we observed the characteristic anti-crossing of the polariton dispersion both in the reflection and photoluminescence spectrum. A Rabi splitting of 18 meV was observed which matched well with our numerical simulation. The diffraction effects of the nano-patterned metasurface also resulted in a highly directional polariton emission. Finally, we showed that the Rabi splitting, the polariton dispersion and the far-field emission pattern could be tailored with subwavelength-scale engineering of the optical meta-atoms. Our platform thus opens the door for the future development of novel, exotic exciton-polariton devices by advanced meta-optical engineering.

physics.optics↗

arXiv2020

Design and Analysis of Extended Depth of Focus Metalenses for Achromatic Computational Imaging

Metasurface optics have demonstrated vast potential for implementing traditional optical components in an ultra-compact and lightweight form factor. Metasurface lenses, also called metalenses, however, suffer from severe chromatic aberrations, posing serious limitations on their practical use. Existing approaches for circumventing such aberrations via dispersion engineering are limited to small apertures and often entails multiple scatterers per unit cell with small feature sizes. Here, we present an alternative technique to mitigate chromatic aberration and demonstrate high-quality, full-color imaging using extended depth of focus (EDOF) metalenses and computational reconstruction. Previous EDOF metalenses relied on cubic phase masks that induced asymmetric artifacts in images, whereas here we demonstrate the use of symmetric phase masks that can improve subsequent image quality, including logarithmic-aspherical, and shifted axicon masks. Our work will inspire further development in achromatic metalenses beyond dispersion engineering and open new research avenues on hybrid optical-digital metasurface systems.

physics.optics↗

arXiv2018

Deterministic positioning of colloidal quantum dots on silicon nitride nanobeam cavities

Engineering an array of precisely located cavity-coupled active media poses a major experimental challenge in the field of hybrid integrated photonics. We deterministically position solution processed colloidal quantum dots (QDs) on high quality-factor silicon nitride nanobeam cavities and demonstrate light-matter coupling. By lithographically defining a window on top of an encapsulated cavity that is cladded in a polymer resist, and spin coating QD solution, we can precisely control the placement of the QDs, which subsequently couple to the cavity. We show that the number of QDs coupled to the cavity can be controlled by the size of the window. Furthermore, we demonstrate Purcell enhancement and saturable photoluminescence in this QD-cavity platform. Finally, we deterministically position QDs on a photonic molecule and observe QD-coupled cavity super-modes. Our results pave the way for controlling the number of QDs coupled to a cavity by engineering the window size, and the QD dimension, and will allow advanced studies in cavity enhanced single photon emission, ultralow power nonlinear optics, and quantum many-body simulations with interacting photons.

physics.optics↗

arXiv2017

Encapsulated silicon nitride nanobeam cavity for nanophotonics using layered materials

Most existing implementations of silicon nitride photonic crystal cavities rely on suspended membranes due to the low refractive index of silicon nitride. Such floating membranes are not mechanically robust, making them suboptimal for developing a hybrid optoelectronic platform where new materials, such as layered 2D materials, are transferred on a pre-existing optical cavity. To address this issue, we propose a silicon nitride nanobeam resonator design where the silicon nitride membrane is encapsulated by material with a refractive index of ~1.5, such as silicon dioxide or PMMA. The theoretically calculated quality factor of the cavities can be as large as 100,000 , with a mode-volume of 2.5 times the cubic wavelength. We fabricated the cavity, and measured the transmission spectrum with highest quality factor of 7000. We also successfully transferred monolayer tungsten diselenide on the encapsulated silicon nitride nanobeam, and demonstrated coupling of the cavity with the monolayer exciton and the defect emissions.

cond-mat.mes-hall↗