arXiv subjects

Eric Howard

Publications and source records attributed to Eric Howard.

12 recordsLinked to original sources

arXiv2026

Criticality in Neural Network Function Space through Wilsonian Fixed Points and Finite-Width Corrections

Neural networks can be studied not only as parameterized computational models but also as probability distributions over functions. In this paper we develop a Wilsonian interpretation of criticality in the neural network-quantum field theory correspondence, treating the infinite width Gaussian-process limit as a free field fixed point and finite width corrections as perturbations that create non-Gaussian interactions. In this way, we do not see the departure from infinite width as a small approximation error but as the process by which interaction, complexity, expressivity and phase-like behaviour enter neural network function space. Width, depth, activation nonlinearity, initialization variance, and training dynamics are considered as control parameters that change the effective action of the network ensemble. The critical regime is when the higher-order connected correlation functions become non-negligible, and when the finite width operators become relevant or marginal scaling factors, and when the function distribution becomes sensitive to scale-dependent structure. There we can view overparameterization as suppressing a relationship of interacting terms and we find that the critical structure of finite neural networks is given by finite-width effects. This framework is a theoretical basis for studying trainability, generalization, and architectural universality of neural network functions through Wilsonian fixed points, perturbations, and critical surfaces.

cond-mat.dis-nn↗

arXiv2026

Dirac-Line Criticality and Emergent Horizons in Weyl Lifshitz Transitions

Type-II Weyl fermions may emerge behind the event horizon of black holes. We employ the Painlev\'e-Gullstrand metric to study the surface of the Lifshitz transition at the horizon, equivalent to the interface separating the type-I and type-II Weyl states. We find several analogies between the black hole horizon and the transformation of type-I to type-II Weyl fermions through the Dirac line. We analyze the symmetry-protected topological order at the Lifshitz transition originating in semimetals. The emergence of Hawking radiation in Weyl semimetals is discussed. We show that the transition state from type-I to type-II Dirac fermions can be viewed as a black-hole horizon, which exhibits unique characteristics, including a Dirac-line Fermi surface with a nontrivial topological invariant and a critical chiral anomaly effect.

cond-mat.mes-hall↗

arXiv2026

Hybrid Classical--Quantum Optimization of Wireless Routing Using QAOA and Quantum Walks

Routing in wireless communication networks is shaped by mobility, interference, congestion, and competing service requirements, making route selection a high-dimensional constrained optimization problem rather than a simple shortest-path task. This paper investigates the use of hybrid classical--quantum methods for wireless routing, focusing on the Quantum Approximate Optimization Algorithm (QAOA) and quantum walks as candidate mechanisms for exploring complex routing spaces. The paper examines how wireless routing can be expressed as a constrained graph optimization problem in which routing objectives, flow constraints, connectivity requirements, and interference effects are mapped into quantum-compatible Hamiltonian representations. It then discusses how these approaches can be integrated into a hybrid architecture in which classical systems perform network monitoring, graph construction, pre-processing, and deployment, while quantum subroutines are used for selected optimization components. The analysis shows that the potential value of quantum routing lies primarily in the treatment of difficult combinatorial subproblems rather than end-to-end replacement of classical routing frameworks. The paper also highlights practical limitations arising from state preparation, constraint encoding, oracle construction, hardware noise, limited qubit resources, and hybrid execution overhead. It is argued that any meaningful near-term advantage will depend on careful problem decomposition, compact encoding, and tight classical--quantum integration.

quant-ph↗

arXiv2025

Quantum Bayesian inference with Suport vector states for intrusion detection

We present a quantum Bayesian inference method for intrusion detection, using explicitly constructed quantum circuits and statevector simulation. Prior and conditional probabilities are encoded via unitary gates, and posterior distributions are extracted through symbolic post-selection. Applied to a scenario with network spikes, system vulnerabilities, and false alarms, the method yields joint, marginal, and conditional probabilities aligned with causal structure. Our results demonstrate the feasibility and interpretability of quantum-native inference for information security applications

quant-ph↗

arXiv2024

Detection of Dark Matter using levitated nanoparticles within a Bessel-Gaussian beam via Yukawa coupling

We present a novel experimental approach to detect dark matter by probing Yukawa interactions, commonly referred to as a fifth force, between dark matter and baryonic matter. Our method involves optically levitating nanoparticles within a Bessel-Gaussian beam to detect minute forces exerted by potential dark matter interaction with test masses. The non-diffracting properties of Bessel-Gaussian beams, combined with feedback cooling techniques, provide exceptional sensitivity to small perturbations in the motion of the nanoparticles. This setup allows for precise control over trapping conditions and enhances the detection sensitivity to forces on the order of $10^{-18}$ N. We explore the parameter space of the Yukawa interaction, focusing on the coupling strength ($\alpha$) and interaction range ($\lambda$), and discuss the potential of this experiment to place new constraints on dark matter couplings, complementing existing direct detection methods.

hep-ph↗

arXiv2024

Mutual information and correlation measures in holographic RG flows

This paper investigates the behavior of mutual information, entanglement negativity, and multipartite correlations in holographic RG flows, particularly during phase transitions. Mutual information provides a UV-finite measure of total correlations between subsystems, while entanglement negativity and multipartite correlations offer finer insights into quantum structures, especially near critical points. Through numerical simulations, we show that while mutual information remains relatively smooth, both entanglement negativity and multipartite correlations exhibit sharp changes near phase transitions. These results support the hypothesis that multipartite correlations play a dominant role in signaling critical phenomena in strongly coupled quantum systems.

quant-ph↗

arXiv2024

Finite-temperature CFT in Rindler Vacuum

This paper investigates the finite-temperature behavior of Conformal Field Theory (CFT) in Rindler vacuum, focusing on the relation between acceleration and thermality in quantum field theory. We illustrate how uniformly accelerated observers perceive the vacuum as a thermal state via Unruh effect, shedding light on the thermal properties of Rindler horizon. Through numerical simulations of the heat kernel, Unruh temperature, Planck distribution, and detector response, we demonstrate that acceleration enhances the thermal characteristics of quantum fields. These results provide important insights into horizon-induced thermality, with significant implications for black hole thermodynamics and quantum gravity.

gr-qc↗

arXiv2024

Autoencoder-based learning of Quantum phase transitions in the two-component Bose-Hubbard model

This paper investigates the use of autoencoders and machine learning methods for detecting and analyzing quantum phase transitions in the Two-Component Bose-Hubbard Model. By leveraging deep learning models such as autoencoders, we investigate latent space representations, reconstruction error analysis, and cluster distance calculations to identify phase boundaries and critical points. The study is supplemented by dimensionality reduction techniques such as PCA and t-SNE for latent space visualization. The results demonstrate the potential of autoencoders to describe the dynamics of quantum phase transitions.

cond-mat.quant-gas↗

arXiv2024

Simulating black hole quantum dynamics on an optical lattice using the complex Sachdev-Ye-Kitaev model

We propose a low energy model for simulating an analog black hole on an optical lattice using ultracold atoms. Assuming the validity of the holographic principle, we employ the Sachdev-Ye-Kitaev (SYK) model, which describes a system of randomly infinite range interacting fermions, also conjectured to be an exactly solvable UV-complete model for an extremal black hole in a higher dimensional Anti-de Sitter (AdS) dilaton gravity. At low energies, the SYK model exhibits an emergent conformal symmetry and is dual to the extremal black hole solution in near AdS2 spacetime. Furthermore, we show how the SYK maximally chaotic behaviour at large N limit, found to be dual to a gauge theory in higher dimensions, can also be employed as a non-trivial investigation tool for the holographic principle. The proposed setup is a theoretical platform to realize the SYK model with relevant exotic effects and behaviour at low energies as a highly non-trivial example of the AdS/CFT duality and a framework for studying black holes.

physics.gen-ph↗

arXiv2021

High-precision search for dark photon dark matter with the Parkes Pulsar Timing Array

The nature of dark matter remains obscure in spite of decades of experimental efforts. The mass of dark matter candidates can span a wide range, and its coupling with the Standard Model sector remains uncertain. All these unknowns make the etection of dark matter extremely challenging. Ultralight dark matter, with $m \sim10^{-22}$ eV, is proposed to reconcile the disagreements between observations and predictions from simulations of small-scale structures in the cold dark matter paradigm, while remaining consistent with other observations. Because of its large de Broglie wavelength and large local occupation number within galaxies, ultralight dark matter behaves like a coherently oscillating background field with an oscillating frequency dependent on its mass. If the dark matter particle is a spin-1 dark photon, such as the $U(1)_B$ or $U(1)_{B-L}$ gauge boson, it can induce an external oscillating force and lead to displacements of test masses. Such an effect would be observable in the form of periodic variations in the arrival times of radio pulses from highly stable millisecond pulsars. In this study, we search for evidence of ultralight dark photon dark matter (DPDM) using 14-year high-precision observations of 26 pulsars collected with the Parkes Pulsar Timing Array. While no statistically significant signal is found, we place constraints on coupling constants for the $U(1)_B$ and $U(1)_{B-L}$ DPDM. Compared with other experiments, the limits on the dimensionless coupling constant $\epsilon$ achieved in our study are improved by up to two orders of magnitude when the dark photon mass is smaller than $3\times10^{-22}$~eV ($10^{-22}$~eV) for the $U(1)_{B}$ ($U(1)_{B-L}$) scenario.

hep-ph↗

arXiv2021

Constraining cosmological phase transitions with the Parkes Pulsar Timing Array

A cosmological first-order phase transition is expected to produce a stochastic gravitational wave background. If the phase transition temperature is on the MeV scale, the power spectrum of the induced stochastic gravitational waves peaks around nanohertz frequencies, and can thus be probed with high-precision pulsar timing observations. We search for such a stochastic gravitational wave background with the latest data set of the Parkes Pulsar Timing Array. We find no evidence for a Hellings-Downs spatial correlation as expected for a stochastic gravitational wave background. Therefore, we present constraints on first-order phase transition model parameters. Our analysis shows that pulsar timing is particularly sensitive to the low-temperature ($T \sim 1 - 100$ MeV) phase transition with a duration $(\beta/H_*)^{-1}\sim 10^{-2}-10^{-1}$ and therefore can be used to constrain the dark and QCD phase transitions.

astro-ph.CO↗

arXiv2018

Holographic Renormalization with Machine learning

At low energies, the microscopic characteristics and changes of physical systems as viewed at different distance scales are described by universal scale invariant properties investigated by the Renormalization Group (RG) apparatus, an efficient tool used to deal with scaling problems in effective field theories. We employ an information-theoretic approach in a deep learning setup by introducing an artificial neural network algorithm to map and identify new physical degrees of freedom. Using deep learning methods mapped to a genuine field theory, we develop a mechanism capable to identify relevant degrees of freedom and induce scale invariance without prior knowledge about a system. We show that deep learning algorithms that use an RG-like scheme to learn relevant features from data could help to understand the nature of the holographic entanglement entropy and the holographic principle in context of the AdS/CFT correspondence.

physics.gen-ph↗