Search arXiv⌕ Search

arXiv subjects

Michael Fowler

Publications and source records attributed to Michael Fowler.

9 recordsLinked to original sources
arXiv2026

Mode-Selective and Anharmonicity-Controlled Energy Transport in Cavity-Coupled Water

Recent experiments demonstrate the modification of chemical dynamics via cavity-enhanced vibrational energy transport. Here, we provide a microscopic account of both photonic and mode-selective energy transport using direct mesoscale on-the-fly simulations and provide the mechanistic principles of cavity-modified transport under vibrational strong coupling. We find that molecular anharmonicity plays a crucial role in dictating photonic transport, and driving-dependent photonic localization occurs when coupling cavity modes to a highly anharmonic mode of the molecular system. We demonstrate this in cavity-coupled water by tuning the photon frequency (at normal incidence) close to either the harmonic (or weakly anharmonic) bending mode or the anharmonic stretching modes of water. We confirm our understanding using a simple model system by reproducing the photonic transport and its localization. We also demonstrate that the diffusion of mode-selective temperature, quantified via the variance of the H-O-H bond angle or of the O-H bond length, is highly dependent on the cavity photon frequency. We show that the cavity photon frequency can be used as a tuning knob to achieve and control mode-selective energy transport. We also provide a simple analytical understanding of this phenomenon. Our results highlight the rich dynamical interplay of molecular and photonic degrees of freedom that persist in real atomistic systems.

physics.optics↗
arXiv2026

A diagrammatic proof-theoretic semantics for the Greimas semiotic square

We develop a diagrammatic proof system for a fragment of structural semantics inspired by the Greimas semiotic square, using spider diagrams as the underlying formalism. The basic terms are represented as diagrammatic configurations, and the relations of contradiction and implication are interpreted as transformations governed by a set of inference rules. These transformations are realised as derivations, with proof trees serving as witnesses. Our main result shows that the construction of the four meta-terms can be captured uniformly: each is derivable from a conjunctive pair of basic configurations via a fixed derivation schema composed of contour introduction and habitat transformation rules. This yields a proof-theoretic account of the combinatorial operation underlying meta-term formation, and provides a semantic interpretation of the Greimasian operation `+' as a derivational construction rather than a logical combination. We further show that diagrammatic negation in this setting is not a Boolean complement, but a restricted, zone-determined semantic counter-position, reflecting the relational character of opposition in structural semiotics. The resulting framework provides a compositional, rule-based semantics in which complex configurations are generated constructively from simpler ones. In addition to extending the expressive scope of spider diagram calculi, the system illustrates how diagrammatic reasoning can be used to formalise non-classical semantic operations within a unified inferential setting.

cs.LO↗
arXiv2026

Kleisli semantics and hypergraph composition for Greimasian narrative programs

This article proposes a category-theoretic formalization of Greimasian narrative programs (NPs) that makes their compositional structure mathematically precise. Building on a reconstruction of the actantial model as a categorical schema, we introduce a refined typological schema of actants and derive Set-valued instances corresponding to role-indexed elements of a narrative. NPs are represented within a categorical schema whose morphisms are interpreted using monads on Set. In particular, the List monad provides a Kleisli semantics for modeling non-atomic, list-valued actantial configurations, while the Maybe monad encodes optional dependencies between programs. This yields a minimal representation of narrative programs as structured data with an intrinsic compositional interpretation. To account for the dynamics of narrative formation, we lift these constructions into a diagrammatic setting by freely generating a symmetric monoidal category, and subsequently a hypergraph category, from the set of actants. In this framework, narrative programs act as generators of morphisms, and their composition is realized through wiring diagrams. A narrative trajectory is thereby interpreted as a single composite morphism. This approach provides a unified mathematical framework for structural semiotics, connecting data-level representations of narrative elements with their compositional realization in discourse.

math.CT↗
arXiv2021

A category-theoretic approach to modeling John Cage's Silent piece

We derive a schema of John Cage's meta-work the Silent piece from his compositions 4'33'', 0'00''(4'33'' No. 2), and One3, using the mathematics of category theory within Spivak and Kent's (2012) framework of ontological logs for knowledge representation. A category presentation A of a database that describes an instance of 4'33'' from its premiere in 1952 is translated via two functors into the category presentations B (0'00'') and C (One3). A pushout of B and C along A allows for the presentation of the category S (the meta-work the Silent piece), and a discussion of the category's S-specification and fiber order. Finally, we derive a semantics from the fiber in order to reason on persistent spatio-temporal structures of Cage's Silent piece.

math.GM↗
arXiv2019

Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments

Dynamic spectrum access (DSA) benefits from detection and classification of interference sources including in-network users, out-network users, and jammers that may all coexist in a wireless network. We present a deep learning based signal (modulation) classification solution in a realistic wireless network setting, where 1) signal types may change over time; 2) some signal types may be unknown for which there is no training data; 3) signals may be spoofed such as the smart jammers replaying other signal types; and 4) different signal types may be superimposed due to the interference from concurrent transmissions. For case 1, we apply continual learning and train a Convolutional Neural Network (CNN) using an Elastic Weight Consolidation (EWC) based loss. For case 2, we detect unknown signals via outlier detection applied to the outputs of convolutional layers using Minimum Covariance Determinant (MCD) and k-means clustering methods. For case 3, we extend the CNN structure to capture phase shifts due to radio hardware effects to identify the spoofing signal sources. For case 4, we apply blind source separation using Independent Component Analysis (ICA) to separate interfering signals. We utilize the signal classification results in a distributed scheduling protocol, where in-network (secondary) users employ signal classification scores to make channel access decisions and share the spectrum with each other while avoiding interference with out-network (primary) users and jammers. Compared with benchmark TDMA-based schemes, we show that distributed scheduling constructed upon signal classification results provides major improvements to in-network user throughput and out-network user success ratio.

cs.NI↗
arXiv1997

Nucleation and Growth of the Superconducting Phase in the Presence of a Current

We study the localized stationary solutions of the one-dimensional time-dependent Ginzburg-Landau equations in the presence of a current. These threshold perturbations separate undercritical perturbations which return to the normal phase from overcritical perturbations which lead to the superconducting phase. Careful numerical work in the small-current limit shows that the amplitude of these solutions is exponentially small in the current; we provide an approximate analysis which captures this behavior. As the current is increased toward the stall current J*, the width of these solutions diverges resulting in widely separated normal-superconducting interfaces. We map out numerically the dependence of J* on u (a parameter characterizing the material) and use asymptotic analysis to derive the behaviors for large u (J* ~ u^-1/4) and small u (J -> J_c, the critical deparing current), which agree with the numerical work in these regimes. For currents other than J* the interface moves, and in this case we study the interface velocity as a function of u and J. We find that the velocities are bounded both as J -> 0 and as J -> J_c, contrary to previous claims.

cond-mat.supr-con↗
arXiv1992

Twisted Boundary Conditions and the Adiabatic Ground State for the Attractive XXZ Luttinger Liquid

The one-dimensional attractive lattice fermion gas equivalent to the Heisenberg-Ising spin 1/2 chain is studied for a ring geometry threaded by magnetic flux. We find that for charged fermions having interaction strength $Δ=\cos(π/ p)$ with $p$ {\it noninteger}, the adiabatic ground state is periodic in the magnetic flux threading the chain, with period 2 flux quanta, as found by Shastry and Sutherland for the repulsive case. We find that, at particular values of the threading field, a sequence of initially zero-energy bound states form at the Fermi surface during the adiabatic process, the largest containing $[p]$ (the integer part of $p$) fermions. This largest bound state moves around to the other Fermi point and sequentially unbinds. We find Berry's Phase for the whole process to be $[p] π$. For $p$ {\it integer}, as $Φ$ increases, eventually all the particles in the system go into bound states of size $[p]$. The period in this case is of order the size of the system.

cond-mat↗