arXiv subjects

James Stewart

Publications and source records attributed to James Stewart.

10 recordsLinked to original sources

arXiv2026

CL API: Real-Time Closed-Loop Interactions with Biological Neural Networks

Biological neural networks (BNNs) are increasingly explored for their rich dynamics, parallelism, and adaptive behavior. Beyond understanding their function as a scientific endeavour, a key focus has been using these biological systems as a novel computing substrate. However, BNNs can only function as reliable information-processing systems if inputs are delivered in a temporally and structurally consistent manner. In practice, this requires stimulation with precisely controlled structure, microsecond-scale timing, multi-channel synchronization, and the ability to observe and respond to neural activity in real-time. Existing approaches to interacting with BNNs face a fundamental trade-off: they either depend on low-level hardware mechanisms, imposing prohibitive complexity for rapid iteration, or they sacrifice temporal and structural control, undermining consistency and reproducibility - particularly in closed-loop experiments. The Cortical Labs Application Programming Interface (CL API) enables real-time, sub-millisecond closed-loop interactions with BNNs. Taking a contract-based API design approach, the CL API provides users with precise stimulation semantics, transactional admission, deterministic ordering, and explicit synchronization guarantees. This contract is presented through a declarative Python interface, enabling non-expert programmers to express complex stimulation and closed-loop behavior without managing low-level scheduling or hardware details. Ultimately, the CL API provides an accessible and reproducible foundation for real-time experimentation with BNNs, supporting both fundamental biological research and emerging neurocomputing applications.

q-bio.NC↗

arXiv2025

Quasi-Periodic Pulsations Driven by Structural Oscillations in a Kink-Unstable Flaring Coronal Loop

Twisted coronal loops in the solar atmosphere may become kink-unstable when their magnetic field lines are sufficiently twisted. This instability can trigger magnetic reconnection, leading to the emission of electromagnetic radiation, which manifests as a solar flare. Previous research has demonstrated that oscillations in microwave emissions, resembling observed quasi-periodic pulsations (QPPs), can be generated by the reconnecting loop. Our aim is to investigate the relationship between the oscillations of the loop and these microwave pulsations. Using 3D magnetohydrodynamical simulations, we examine two models: a straight loop in a uniform-density atmosphere and a curved loop in a gravitationally stratified atmosphere. Using new methodology, we extract the reconnecting loop-top from both models and identify structural oscillations. We then compare these oscillations with the gyrosynchrotron (GS) radiation emitted from the simulations, which is forward-modelled using a radiative transfer code. We find that oscillations in the GS emissions are driven by sausage and kink-mode oscillations. However, the relationship between the oscillation frequencies of the GS emission and the identified loop oscillation modes is complex. The dominant mode in the former may result from interference between sausage-mode and kink-mode oscillations or entirely different mechanisms. Results such as these increase our understanding of the time-dependent behaviour of solar flares and lay the groundwork for potential diagnostic tools that could be used to determine physical parameters within a flaring loop

astro-ph.SR↗

arXiv2024

The effects of resistivity on oscillatory reconnection and consequences for solar flare Quasi Periodic Pulsations

Quasi-periodic pulsations (QPPs) are often observed in flare emissions. While these may reveal much about the time-dependent reconnection involved in flare energy release, the underlying mechanisms are still poorly understood. In this paper, we use 2D magnetohydrodynamic simulations to investigate the magnetic reconnection in two merging flux ropes, focusing on the effects of the resistivity on the time variation of the reconnection. We consider both uniform resistivity and current-dependent anomalous resistivity profiles. Our findings reveal that resistivity plays a critical role in controlling the reconnection dynamics, including reconnection rate oscillations and the rate of decay of the reconnection rate. Resistivity also influences the oscillations in emitted gyrosynchrotron radiation. However, in contrast to this strong influence of resistivity on reconnection rates, we observed a different behaviour for the emitted waves, whose frequencies are almost independent of resistivity variations.

astro-ph.SR↗

arXiv2022

Fast mixing via polymers for random graphs with unbounded degree

The polymer model framework is a classical tool from statistical mechanics that has recently been used to obtain approximation algorithms for spin systems on classes of bounded-degree graphs; examples include the ferromagnetic Potts model on expanders and on the grid. One of the key ingredients in the analysis of polymer models is controlling the growth rate of the number of polymers, which has been typically achieved so far by invoking the bounded-degree assumption. Nevertheless, this assumption is often restrictive and obstructs the applicability of the method to more general graphs. For example, sparse random graphs typically have bounded average degree and good expansion properties, but they include vertices with unbounded degree, and therefore are excluded from the current polymer-model framework. We develop a less restrictive framework for polymer models that relaxes the standard bounded-degree assumption, by reworking the relevant polymer models from the edge perspective. The edge perspective allows us to bound the growth rate of the number of polymers in terms of the total degree of polymers, which in turn can be related more easily to the expansion properties of the underlying graph. To apply our methods, we consider random graphs with unbounded degrees from a fixed degree sequence (with minimum degree at least 3) and obtain approximation algorithms for the ferromagnetic Potts model, which is a standard benchmark for polymer models. Our techniques also extend to more general spin systems.

cs.DS↗

arXiv2021

Fast algorithms for general spin systems on bipartite expanders

A spin system is a framework in which the vertices of a graph are assigned spins from a finite set. The interactions between neighbouring spins give rise to weights, so a spin assignment can also be viewed as a weighted graph homomorphism. The problem of approximating the partition function (the aggregate weight of spin assignments) or of sampling from the resulting probability distribution is typically intractable for general graphs. In this work, we consider arbitrary spin systems on bipartite expander $Δ$-regular graphs, including the canonical class of bipartite random $Δ$-regular graphs. We develop fast approximate sampling and counting algorithms for general spin systems whenever the degree and the spectral gap of the graph are sufficiently large. Our approach generalises the techniques of Jenseen et al. and Chen et al. by showing that typical configurations on bipartite expanders correspond to "bicliques" of the spin system; then, using suitable polymer models, we show how to sample such configurations and approximate the partition function in $\tilde{O}(n^2)$ time, where $n$ is the size of the graph.

cs.DS↗

arXiv2021

Fast algorithms at low temperatures via Markov chains

We define a discrete-time Markov chain for abstract polymer models and show that under sufficient decay of the polymer weights, this chain mixes rapidly. We apply this Markov chain to polymer models derived from the hard-core and ferromagnetic Potts models on bounded-degree (bipartite) expander graphs. In this setting, Jenssen, Keevash and Perkins (2019) recently gave an FPTAS and an efficient sampling algorithm at sufficiently high fugacity and low temperature respectively. Their method is based on using the cluster expansion to obtain a complex zero-free region for the partition function of a polymer model, and then approximating this partition function using the polynomial interpolation method of Barvinok. Our approach via the polymer model Markov chain circumvents the zero-free analysis and the generalization to complex parameters, and leads to a sampling algorithm with a fast running time of $O(n \log n)$ for the Potts model and $O(n^2 \log n)$ for the hard-core model, in contrast to typical running times of $n^{O(\log Δ)}$ for algorithms based on Barvinok's polynomial interpolation method on graphs of maximum degree $Δ$. We finally combine our results for the hard-core and ferromagnetic Potts models with standard Markov chain comparison tools to obtain polynomial mixing time for the usual spin Glauber dynamics restricted to even and odd or `red' dominant portions of the respective state spaces.

cs.DS↗

arXiv2021

Modeling impurity concentrations in liquid argon detectors

Impurities in noble liquid detectors used for neutrino and dark matter experiments can significantly impact the quality of data. We present an experimentally verified model for describing the dynamics of impurity distributions in liquid argon (LAr) detectors. The model considers sources, sinks, and transport of impurities within and between the gas and liquid argon phases. Measurements of oxygen concentrations in a 20-L LAr multi-purpose test stand are compared to calculations made with this model to show that an accurate description of the concentrations under various operational conditions can be obtained. A result of this analysis is a determination of Henry's coefficient for oxygen in LAr. These calculations also show that some processes have small effects on the impurity dynamics and excluding them yields a solution as a sum of two exponential terms. This solution provides a simple way to extract Henry's coefficient with negligible approximation error. It is applied to the data and the Henry's coefficient for oxygen in LAr is obtained as 0.84$^{+0.09}_{-0.05}$, consistent with literature results. Based on the analysis of the data with the model, we further suggest that, for a large liquid argon detector, barriers to flow ("baffles") installed in the gas phase to restrict flow can help reduce the ultimate impurity concentration in the LAr.

physics.ins-det↗

arXiv2016

A 20-Liter Test Stand with Gas Purification for Liquid Argon Research

We describe the design of a 20-liter test stand constructed to study fundamental properties of liquid argon (LAr). This system utilizes a simple, cost-effective gas argon (GAr) purification to achieve high purity, which is necessary to study electron transport properties in LAr. An electron drift stack with up to 25 cm length is constructed to study electron drift, diffusion, and attachment at various electric fields. A gold photocathode and a pulsed laser are used as a bright electron source. The operational performance of this system is reported.

physics.ins-det↗

arXiv2016

Measurement of Longitudinal Electron Diffusion in Liquid Argon

We report the measurement of longitudinal electron diffusion coefficients in liquid argon for electric fields between 100 and 2000 V/cm with a gold photocathode as a bright electron source. The measurement principle, apparatus, and data analysis are described. Our results, which are consistent with previous measurements in the region between 100 to 350 V/cm [1] , are systematically higher than the prediction of Atrazhev-Timoshkin[2], and represent the world's best measurement in the region between 350 to 2000 V/cm. The quantum efficiency of the gold photocathode, the drift velocity and longitudinal diffusion coefficients in gas argon are also presented.

physics.ins-det↗

arXiv2009

Report on the Depth Requirements for a Massive Detector at Homestake

This report provides the technical justification for locating a large detector underground in a US based Deep Underground Science and Engineering Laboratory. A large detector with a fiducial mass in the mega-ton scale will most likely be a multipurpose facility. The main physics justification for such a device is detection of accelerator generated neutrinos, nucleon decay, and natural sources of neutrinos such as solar, atmospheric and supernova neutrinos. In addition to the physics justification there are practical issues regarding the existing infrastructure at Homestake, and the stress characteristics of the Homestake rock formations. The depth requirements associated with the various physics processes are reported for water Cherenkov and liquid argon detector technologies. While some of these physics processes can be adequately studied at shallower depths, none of them require a depth greater than 4300 mwe which corresponds to the 4850 ft level at Homestake. It is very important to note that the scale of the planned detector is such that even for accelerator neutrino detection (which allows one to use the accelerator duty factor to eliminate cosmics) a minimum depth is needed to reduce risk of contamination from cosmic rays. After consideration of the science and the practical issues regarding the Homestake site, we strongly recommend that the geotechnical studies be commenced at the 4850ft level in a timely manner.

hep-ex↗