Explore Mathematical Sciences With AIP Publishing

Discover our extensive collection of journals, conference proceedings, and books that span Mathematical Sciences and its intersections with other disciplines.

As your partner in publishing, whether you’re just beginning your journey or have years of experience, we’re here to provide you with the best home for your work and the tools and resources you need to elevate and amplify your research.

Featured Journals

Journals dedicated to research in Mathematical Sciences:

Journal of Mathematical Physics

One of the most highly cited journals in mathematical physics    

1.2 Impact Factor*
22.8 Years cited half-life*
2.2 CiteScore™†
190+ Avg. views/article annually
205 Days avg. time to acceptance
90 Days avg. time to first decision
Topics covered: Mathematical physics, quantum mechanics, statistical physics, classical mechanics
Article types: Articles, Reviews
Access type: Subscription with open access option
Indexed In: Web of Science, Scopus

Chaos

An Interdisciplinary Journal of Nonlinear Science

2.7 Impact Factor*
5.3 Years cited half-life*
5.2 CiteScore™†
385+ Avg. views/article annually
107 Days avg. time to acceptance
35 Days avg. time to first decision
Topics covered: Nonlinear dynamics, mathematical physics, interdisciplinary physics, statistical physics, society and organization
Article types: Articles, Reviews, Perspectives
Access type: Subscription with open access option
Indexed In: Web of Science, Scopus

Interdisciplinary Journals

Journals at the intersection of education and related disciplines:

Journal of Applied Physics

Significant results in cutting-edge applied physics

Browse Open Special Topics

Applied Physics Letters

Shaping the future of applied physics

Browse Open Special Topics

The Journal of Chemical Physics

The most cited in chemical physics

Browse Open Special Topics

AIP Advances

A peer-reviewed, open access journal covering all areas of the physical sciences

Browse Open Special Topics

APL Quantum

Bridging fundamental quantum research with technological applications

First Issue Now Online

APL Machine Learning

Machine Learning for Applied Physics
Applied Physics for Machine Learning

Browse Open Special Topics

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More Journals to Explore

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Featured AIP Conference Proceedings

AIP Conference Proceedings has been a trusted publishing partner for more than 40 years, delivering fast, affordable, and versatile publishing for maximum exposure of your meeting’s key research. Below are just a few of the Proceedings that are rooted in Mathematical Sciences research.    

	Preface: Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2022 (ICNAAM-2022)
	Preface: Application of Mathematics in Technical and Natural Sciences: 14th International Conference – AMiTaNS’22
	Preface: 11th Int’l Conference on Mathematical Modeling in Physical Sciences

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Highlighted Research

The elliptic Ginibre ensemble: A unifying approach to local and global statistics for higher dimensions

The elliptic Ginibre ensemble of complex non-Hermitian random matrices allows us to interpolate between the rotationally invariant Ginibre ensemble and the Gaussian unitary ensemble of Hermitian random matrices.

Modified gravity: A unified approach to metric-affine models

The starting point of this work is the original Einstein action, sometimes called the Gamma squared action. Continuing from our previous results, we study various modified theories of gravity following the Palatini approach. The metric and the connection will be treated as independent variables leading to generalized theories, which may contain torsion or non-metricity or both.

Explicit Nth order solutions of Fokas–Lenells equation based on revised Riemann–Hilbert approach

We develop a revised Riemann–Hilbert problem (RHP) to the Fokas–Lenells (FL) equation with a zero boundary condition, satisfying the normalization condition, and the potential of the FL equation is recovered from the asymptotic behavior of RHP when the spectral parameter goes to zero.

Exact solution and coherent states of an asymmetric oscillator with position-dependent mass

We revisit the problem of the deformed oscillator with position-dependent mass [da Costa et al., J. Math. Phys. 62, 092101 (2021)] in the classical and quantum formalisms by introducing the effect of the mass function in both kinetic and potential energies.

On the Cauchy problem for Boltzmann equation modeling a polyatomic gas

In the present article, we consider the Boltzmann equation that models a polyatomic gas by introducing one additional continuous variable, referred to as microscopic internal energy. We establish existence and uniqueness theory in the space homogeneous setting for the full non-linear case, under an extended Grad-type assumption on transition probability rates, which comprises hard potentials for both the relative speed and internal energy with the rate in the interval ⁠, multiplied by an integrable angular part and integrable partition functions.

A memristive neuron and its adaptability to external electric field

Connecting memristors into any neural circuit can enhance its potential controllability under external physical stimuli. Memristive current along a magnetic flux-controlled memristor can estimate the effect of electromagnetic induction on neural circuits and neurons. Here, a charge-controlled memristor is incorporated into one branch circuit of a simple neural circuit to estimate the effect of an external electric field.

Resonance and bifurcation of fractional quintic Mathieu–Duffing system

In this paper, the main subharmonic resonance of the Mathieu–Duffing system with a quintic oscillator under simple harmonic excitation, the route to chaos, and the bifurcation of the system under the influence of different parameters is studied.

Routes toward chaos in a memristor-based Shinriki circuit

In this paper, the complex routes to chaos in a memristor-based Shinriki circuit are discussed semi-analytically via the discrete implicit mapping method.

Reservoir computing as digital twins for nonlinear dynamical systems

We articulate the design imperatives for machine learning based digital twins for nonlinear dynamical systems, which can be used to monitor the “health” of the system and anticipate future collapse. The fundamental requirement for digital twins of nonlinear dynamical systems is dynamical evolution: the digital twin must be able to evolve its dynamical state at the present time to the next time step without further state input—a requirement that reservoir computing naturally meets.

Synchronization of phase oscillators on complex hypergraphs

We study the effect of structured higher-order interactions on the collective behavior of coupled phase oscillators. By combining a hypergraph generative model with dimensionality reduction techniques, we obtain a reduced system of differential equations for the system’s order parameters.

Upcoming Conferences

You’ll find AIP Publishing’s editors and journal managers at these upcoming conferences and events. We hope to see you there!

Materials Research Society (MRS) Fall 2024
Boston, MA USA
December 1 – 6, 2024
Booth 818

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*Data from the 2023 Journal Citation Reports® Science Edition (Clarivate, 2024).
†CiteScore™ 2023 for AIP Publishing Journals Calculated by Scopus