arXiv subjects

Nicholas Wilkins

Publications and source records attributed to Nicholas Wilkins.

9 recordsLinked to original sources

arXiv2026

Quantum Steenrod powers and Hamiltonian maps

We prove a series of new results in Hamiltonian dynamics on a general closed symplectic manifold $(M, \omega)$, including: 1. If $M$ admits a Hamiltonian diffeomorphism which is either a pseudo-rotation or has finite order, then $M$ is geometrically uniruled. This resolves a variant of Problem 24 in McDuff--Salamon's list, which predicts an obstruction to the existence of such special Hamiltonian diffeomorphisms in terms of genus zero numerical invariants. 2. If a Hamiltonian possesses a periodic orbit in a non-torsion homology class, then it has infinitely many simple periodic points. The same conclusion holds if the manifold is not geometrically uniruled and the diffeomorphism is minimal for rational Floer homology. These two general results complement the known cases of the Hofer--Zehnder conjecture. 3. If a Hamiltonian diffeomorphism possesses a symplectically degenerate maximum, then it has infinitely many simple periodic points. This resolves an open question which stems from the work of Ginzburg and G\"urel. We also establish new cases of the generic Conley conjecture: infinitely many periodic points for generic Hamiltonian diffeomorphisms. The proofs rely on a systematic application of the integral Hamiltonian Floer theory package developed by the first and fourth author, a K\"unneth isomorphism in equivariant Floer homology, and new quantitative analysis of quantum power maps, which is of independent interest.

math.SG↗

arXiv2024

A survey of equivariant operations on quantum cohomology for symplectic manifolds

In this survey paper, we will collate various different ideas and thoughts regarding equivariant operations on quantum cohomology (and some in more general Floer theory) for a symplectic manifold. We will discuss a general notion of equivariant quantum operations associated to finite groups, in addition to their properties, examples, and calculations. We will provide a brief connection to Floer theoretic invariants. We then provide abridged descriptions (as per the author's understanding) of work by other authors in the field, along with their major results. Finally we discuss the first step to compact groups, specifically $S^1$-equivariant operations. Contained within this survey are also a sketch of the idea of mod-$p$ pseudocycles, and an in-depth appendix detailing the author's understanding of when one can define these equivariant operations in an additive way.

math.SG↗

arXiv2023

$S^1$-localisation by pseudocycles, lifts to $S^1$-localisation of moduli spaces, and application to invariants of $S^1$-equivariant symplectic cohomology

We demonstrate a way to apply $S^1$-localisation to moduli spaces of holomorphic curves. We first prove a reinterpretation of Atyiah-Bott $S^1$-localisation, called {\it localisation by pseudocycles} (LbP), for a smooth semifree $S^1$-action on a manifold. We demonstrate that, for certain moduli spaces of holomorphic curves parametrised by some stratum of the homotopy quotient of a manifold, we may ``lift" the LbP procedure from the parameter space to the moduli space. As an application we deduce relations between equivariant symplectic classes and Gromov-Witten invariants, thus proving a conjecture of Seidel.

math.SG↗

arXiv2022

The $\mathbb Z/p$-equivariant cohomology of genus zero Deligne-Mumford space with $1+p$ marked points

We prove that the Serre spectral sequence of the fibration $\overline{\mathcal M}_{0, 1+p} \to E\mathbb Z/p \times_{\mathbb Z/p} \overline{\mathcal M}_{0, 1+p} \to B \mathbb Z/p$ collapses at the $E_2$ page. We use this to prove that: for any element of the $\mathbb Z/p$-equivariant cohomology with $\mathbb F_p$-coefficients of genus zero Deligne-Mumford space with $1+p$ marked points, if this element is torsion then it is non-equivariant. This concludes that the only "interesting" $\mathbb Z/p$-equivariant operations are quantum Steenrod power operations.

math.AT↗

arXiv2022

Covariant constancy of quantum Steenrod operations

We prove a relationship between quantum Steenrod operations and the quantum connection. In particular there are operations extending the quantum Steenrod power operations that, when viewed as endomorphisms of equivariant quantum cohomology, are covariantly constant. We demonstrate how this property is used in computations of examples.

math.SG↗

arXiv2021

Quantum Steenrod squares and the equivariant pair-of-pants in symplectic cohomology

We relate the quantum Steenrod square to Seidel's equivariant pair-of-pants product for open convex symplectic manifolds that are either monotone or exact, using an equivariant version of the PSS isomorphism. We proceed similarly for $\mathbb{Z}/2$-equivariant symplectic cohomology, using an equivariant version of the continuation and $c^*$-maps. We prove a symplectic Cartan relation, pointing out the difficulties in stating it. We give a nonvanishing result for the equivariant pair-of-pants product for some elements of $SH^*(T^* S^n)$. We finish by calculating the symplectic square for the negative line bundles $M = \text{Tot}(\mathcal{O}(-1) \rightarrow \mathbb{CP}^m)$, proving an equivariant version of a result due to Ritter.

math.SG↗

arXiv2020

A construction of the quantum Steenrod squares and their algebraic relations

We construct a quantum deformation of the Steenrod square construction on closed monotone symplectic manifolds, based on the work of Fukaya, Betz and Cohen. We prove quantum versions of the Cartan and Adem relations. We compute the quantum Steenrod squares for all CP n and give the means of computation for all toric varieties. As an application, we also describe two examples of blowups along a subvariety, in which a quantum correction of the Steenrod square on the blowup is determined by the classical Steenrod square on the subvariety.

math.SG↗

arXiv2020

Modeling Global Body Configurations in American Sign Language

American Sign Language (ASL) is the fourth most commonly used language in the United States and is the language most commonly used by Deaf people in the United States and the English-speaking regions of Canada. Unfortunately, until recently, ASL received little research. This is due, in part, to its delayed recognition as a language until William C. Stokoe's publication in 1960. Limited data has been a long-standing obstacle to ASL research and computational modeling. The lack of large-scale datasets has prohibited many modern machine-learning techniques, such as Neural Machine Translation, from being applied to ASL. In addition, the modality required to capture sign language (i.e. video) is complex in natural settings (as one must deal with background noise, motion blur, and the curse of dimensionality). Finally, when compared with spoken languages, such as English, there has been limited research conducted into the linguistics of ASL. We realize a simplified version of Liddell and Johnson's Movement-Hold (MH) Model using a Probabilistic Graphical Model (PGM). We trained our model on ASLing, a dataset collected from three fluent ASL signers. We evaluate our PGM against other models to determine its ability to model ASL. Finally, we interpret various aspects of the PGM and draw conclusions about ASL phonetics. The main contributions of this paper are

cs.CV↗

arXiv2019

Regression with Uncertainty Quantification in Large Scale Complex Data

While several methods for predicting uncertainty on deep networks have been recently proposed, they do not readily translate to large and complex datasets. In this paper we utilize a simplified form of the Mixture Density Networks (MDNs) to produce a one-shot approach to quantify uncertainty in regression problems. We show that our uncertainty bounds are on-par or better than other reported existing methods. When applied to standard regression benchmark datasets, we show an improvement in predictive log-likelihood and root-mean-square-error when compared to existing state-of-the-art methods. We also demonstrate this method's efficacy on stochastic, highly volatile time-series data where stock prices are predicted for the next time interval. The resulting uncertainty graph summarizes significant anomalies in the stock price chart. Furthermore, we apply this method to the task of age estimation from the challenging IMDb-Wiki dataset of half a million face images. We successfully predict the uncertainties associated with the prediction and empirically analyze the underlying causes of the uncertainties. This uncertainty quantification can be used to pre-process low quality datasets and further enable learning.

cs.LG↗