arXiv subjects

James Inglis

Publications and source records attributed to James Inglis.

7 recordsLinked to original sources

arXiv2026

Fortuity beyond counting: an explicit construction

We reconsider the "fortuity'' mechanism in the D1D5 CFT focusing on the K3 symmetric orbifold. Going beyond the counting of BPS states, we investigate perturbatively how the explicit form of the BPS cohomologies is modified by the twist-two deformations. We calculate the action of the supercharges in the sector $(h,j)=(1,0)$ for different values of the central charge and derive explicit expressions for the primary states. Equipped with this information, we compare some protected three-point couplings in the free and the gravity regime. We show that agreement between the two descriptions imposes non-trivial constraints on the identification of monotone and fortuitous states. In particular, we argue that the map relating theories with different values of the central charge must and can be defined so as to commute with the supercharges that define the cochain complex. We then study the three-point correlators between the fortuitous and monotone states identified in our analysis to assess whether the two sectors are dynamically decoupled. We find an explicit example of a non-vanishing coupling between two monotone and a fortuitous state, providing evidence that the two sectors are dynamically connected.

hep-th↗

arXiv2015

A general framework for stochastic traveling waves and patterns, with application to neural field equations

In this paper we present a general framework in which to rigorously study the effect of spatio-temporal noise on traveling waves and stationary patterns. In particular the framework can incorporate versions of the stochastic neural field equation that may exhibit traveling fronts, pulses or stationary patterns. To do this, we first formulate a local SDE that describes the position of the stochastic wave up until a discontinuity time, at which point the position of the wave may jump. We then study the local stability of this stochastic front, obtaining a result that recovers a well-known deterministic result in the small-noise limit. We finish with a study of the long-time behavior of the stochastic wave.

math.PR↗

arXiv2014

Mean-field limit of a stochastic particle system smoothly interacting through threshold hitting-times and applications to neural networks with dendritic component

In this article we study the convergence of a stochastic particle system that interacts through threshold hitting times towards a novel equation of McKean-Vlasov type. The particle system is motivated by an original model for the behavior of a network of neurons, in which a classical noisy integrate-and-fire model is coupled with a cable equation to describe the dendritic structure of each neuron.

math.PR↗

arXiv2014

Log-Sobolev inequalities for infinite-dimensional Gibbs measures with non-quadratic interactions

We focus on the log-Sobolev inequality for spin systems on the lattice with interactions of higher order than quadratic. We show that if the one-dimensional single-site measure with boundaries satisfies the log-Sobolev inequality uniformly in the boundary conditions then the infinite-dimensional Gibbs measure also satisfies the inequality under appropriate conditions on the phase and the interactions.

math.FA↗

arXiv2013

Stochastic neural field equations: A rigorous footing

We extend the theory of neural fields which has been developed in a deterministic framework by considering the influence spatio-temporal noise. The outstanding problem that we here address is the development of a theory that gives rigorous meaning to stochastic neural field equations, and conditions ensuring that they are well-posed. Previous investigations in the field of computational and mathematical neuroscience have been numerical for the most part. Such questions have been considered for a long time in the theory of stochastic partial differential equations, where at least two different approaches have been developed, each having its advantages and disadvantages. It turns out that both approaches have also been used in computational and mathematical neuroscience, but with much less emphasis on the underlying theory. We present a review of two existing theories and show how they can be used to put the theory of stochastic neural fields on a rigorous footing. We also provide general conditions on the parameters of the stochastic neural field equations under which we guarantee that these equations are well-posed. In so doing we relate each approach to previous work in computational and mathematical neuroscience. We hope this will provide a reference that will pave the way for future studies (both theoretical and applied) of these equations, where basic questions of existence and uniqueness will no longer be a cause for concern.

math.PR↗

arXiv2012

Global solvability of a networked integrate-and-fire model of McKean-Vlasov type

We here investigate the well-posedness of a networked integrate-and-fire model describing an infinite population of neurons which interact with one another through their common statistical distribution. The interaction is of the self-excitatory type as, at any time, the potential of a neuron increases when some of the others fire: precisely, the kick it receives is proportional to the instantaneous proportion of firing neurons at the same time. From a mathematical point of view, the coefficient of proportionality, denoted by $\alpha$, is of great importance as the resulting system is known to blow-up for large values of $\alpha$. In the current paper, we focus on the complementary regime and prove that existence and uniqueness hold for all time when $\alpha$ is small enough.

math.PR↗

arXiv2011

Logarithmic Sobolev inequalities for infinite dimensional Hörmander type generators on the Heisenberg group

The Heisenberg group is one of the simplest sub-Riemannian settings in which we can define non-elliptic Hörmander type generators. We can then consider coercive inequalities associated to such generators. We prove that a certain class of nontrivial Gibbs measures with quadratic interaction potential on an infinite product of Heisenberg groups satisfy logarithmic Sobolev inequalities.

math.FA↗