Journal of Complexity

Aims & Scope

The multidisciplinary Journal of Complexity publishes original research papers that contain substantial mathematical results on complexity as broadly conceived.

Outstanding review papers will also be published.

In the area of computational complexity, the focus is on complexity over the reals, with the emphasis on lower bounds and optimal algorithms.

The Journal of Complexity also publishes articles that provide major new algorithms or make important progress on upper bounds.

Other models of computation, such as the Turing machine model, are also of interest.

Computational complexity results in a wide variety of areas are solicited.

Areas Include: • Approximation theory • Biomedical computing • Compressed computing and sensing • Computational finance • Computational number theory • Computational stochastics • Control theory • Cryptography • Design of experiments • Differential equations • Discrete problems • Distributed and parallel computation • High and infinite-dimensional problems • Information-based complexity • Inverse and ill-posed problems • Machine learning • Markov chain Monte Carlo • Monte Carlo and quasi-Monte Carlo • Multivariate integration and approximation • Noisy data • Nonlinear and algebraic equations • Numerical analysis • Operator equations • Optimization • Quantum computing • Scientific computation • Tractability of multivariate problems • Vision and image understanding.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.8
2024	1.80

Journal Rank

Year	Value
2024	6210

Journal Citation Indicator

Year	Value
2024	235

SJR (SCImago Journal Rank)

Year	Value
2024	0.850

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	57

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Decoding of Reed Solomon Codes beyond the Error-Correction Bound

  Citation: 498

  Authors: Madhu

• When Are Quasi-Monte Carlo Algorithms Efficient for High Dimensional Integrals?

  Citation: 433

  Authors: Ian H, Henryk

• Deterministic constructions of compressed sensing matrices

  Citation: 419

  Authors: Ronald A.

• On the capabilities of multilayer perceptrons

  Citation: 278

  Authors: Eric B

• Explicit Cost Bounds of Algorithms for Multivariate Tensor Product Problems

  Citation: 243

  Authors: G.W., H.

• On theL2-Discrepancy for Anchored Boxes

  Citation: 234

  Authors: Jiřı́

• Elastic-net regularization in learning theory

  Citation: 226

  Authors: Christine, Ernesto, Lorenzo

• The covering number in learning theory

  Citation: 210

  Authors: Ding-Xuan

• Do numerical orbits of chaotic dynamical processes represent true orbits?

  Citation: 196

  Authors: Stephen M, James A, Celso

• An encyclopaedia of cubature formulas

  Citation: 193

  Authors: Ronald

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