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

Utilizing mathematics methods to drive physics forward

1.4 Impact Factor*
23.6 Years cited half-life*
2.4 CiteScore™†
110+ Avg. views/article annually
225 Days avg. time to acceptance^‡
98 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

Browse Special Topics Now Online

Chaos

An Interdisciplinary Journal of Nonlinear Science

3.2 Impact Factor*
5.4 Years cited half-life*
4.8 CiteScore™†
230+ Avg. views/article annually
107 Days avg. time to acceptance^‡
31 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

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Interdisciplinary Journals

Journals at the intersection of mathematical sciences and related disciplines:

Journal of Applied Physics

Significant results in cutting-edge applied physics

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Applied Physics Letters

Shaping the future of applied physics for over 60 years

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APL Computational Physics

Showcasing the transformative impact of computation across all physical science

First Issue Now Online

APL Engineering Physics

Physicists study the world as it is. Engineering physicists create the world that has never been

Now Open for Submissions

The Journal of Chemical Physics

The most cited in chemical physics

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AIP Advances

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

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APL Quantum

Bridging fundamental quantum research with technological applications

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APL Machine Learning

Machine Learning for Applied Physics
Applied Physics for Machine Learning

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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

Resilience of transportation infrastructure networks to road failures

Delay embedding methods are a staple tool in the field of time series analysis and prediction. However, the selection of embedding parameters can have a big impact on the resulting analysis. This has led to the creation of a large number of methods to optimize the selection of parameters such as embedding lag.

Rate-induced biosphere collapse in the Daisyworld model

There is much interest in the phenomenon of rate-induced tipping, where a system changes abruptly when forcings change faster than some critical rate. Here, we demonstrate and analyze rate-induced tipping in the classic “Daisyworld” model.

Synchronization in spiking neural networks with short and long connections and time delays

Synchronization is fundamental for information processing in oscillatory brain networks and is strongly affected by time delays via signal propagation along long fibers. Their effect, however, is less evident in spiking neural networks given the discrete nature of spikes.

Removability of the fundamental singularity for the heat equation and its consequences

We prove the necessary and sufficient condition for the removability of the fundamental singularity, and equivalently for the unique solvability of the singular Dirichlet problem for the heat equation. In the measure-theoretical context the criterion determines whether the h-parabolic measure of the singularity point is null or positive.

Connecting stochastic optimal control and reinforcement learning

In this paper the connection between stochastic optimal control and reinforcement learning is investigated. Our main motivation is to apply importance sampling to sampling rare events which can be reformulated as an optimal control problem.

Quantum geodesics in quantum mechanics

We show that the standard Heisenberg algebra of quantum mechanics admits a noncommutative differential calculus Ω1 depending on the Hamiltonian p2/2m + V(x), and a flat quantum connection ∇ with torsion such that a previous quantum-geometric formulation of flow along autoparallel curves (or “geodesics”) is exactly Schrödinger’s equation.

Large-range tuning and stabilization of the optical transition of diamond tin-vacancy centers by in situ strain control

The negatively charged tin-vacancy (SnV−) center in diamond has emerged as a promising platform for quantum computing and quantum networks. To connect SnV− qubits in large networks, in situ tuning and stabilization of their optical transitions are essential to overcome static and dynamic frequency offsets induced by the local environment.

Dynamic phase change materials with extended surfaces

Phase change materials (PCMs) present opportunities for efficient thermal management due to their high latent heat of melting. However, a fundamental challenge for PCM cooling is the presence of a growing liquid layer of relatively low thermal conductivity melted PCM that limits heat transfer.

CREST—A program for the exploration of low-energy molecular chemical space

Conformer–rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities.

Determining internal coordinate sets for optimal representation of molecular vibration

Arising from the harmonic approximation in solving the vibrational Schrödinger equation, normal modes dissect molecular vibrations into distinct degrees of freedom. Normal modes are widely used as they give rise to descriptive vibrational notations and are convenient for expanding anharmonic potential energy surfaces as an alternative to higher-order Taylor series representations.

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Special Topics for Open Submissions
Browse our Special Topics now accepting papers that capture new insights into emerging fields and disciplines across the physical sciences.

*Data from the 2024 Journal Citation Reports® Science Edition (Clarivate, 2025).
†CiteScore™ 2024 for AIP Publishing Journals Calculated by Scopus
‡Publication speeds vary depending on article type