Astrophysics General
Phenomenology of early universe, cosmic microwave background, cosmological parameters, primordial element abundances, extragalactic distance scale, large-scale structure of the universe. Groups, superclusters, voids, intergalactic medium. Particle astrophysics: dark energy, dark matter, baryogenesis, leptogenesis, inflationary models, reheating, monopoles, WIMPs, cosmic strings, primordial black holes, cosmological gravitational radiation.
Interplanetary medium, planetary physics, planetary astrobiology, extrasolar planets, comets, asteroids, meteorites. Structure and formation of the solar system
Phenomena pertaining to galaxies or the Milky Way. Star clusters, HII regions and planetary nebulae, the interstellar medium, atomic and molecular clouds, dust. Stellar populations. Galactic structure, formation, dynamics. Galactic nuclei, bulges, disks, halo. Active Galactic Nuclei, supermassive black holes, quasars. Gravitational lens systems. The Milky Way and its contents
Cosmic ray production, acceleration, propagation, detection. Gamma ray astronomy and bursts, X-rays, charged particles, supernovae and other explosive phenomena, stellar remnants and accretion systems, jets, microquasars, neutron stars, pulsars, black holes
Detector and telescope design, experiment proposals. Laboratory Astrophysics. Methods for data analysis, statistical methods. Software, database design
White dwarfs, brown dwarfs, cataclysmic variables. Star formation and protostellar systems, stellar astrobiology, binary and multiple systems of stars, stellar evolution and structure, coronas. Central stars of planetary nebulae. Helioseismology, solar neutrinos, production and detection of gravitational radiation from stellar systems
Glasses and spin glasses; properties of random, aperiodic and quasiperiodic systems; transport in disordered media; localization; phenomena mediated by defects and disorder; neural networks
Semiconducting nanostructures: quantum dots, wires, and wells. Single electronics, spintronics, 2d electron gases, quantum Hall effect, nanotubes, graphene, plasmonic nanostructures.
Techniques, synthesis, characterization, structure. Structural phase transitions, mechanical properties, phonons. Defects, adsorbates, interfaces
Ultracold atomic and molecular gases, Bose-Einstein condensation, Feshbach resonances, spinor condensates, optical lattices, quantum simulation with cold atoms and molecules, macroscopic interference phenomena
Membranes, polymers, liquid crystals, glasses, colloids, granular matter
Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
Quantum magnetism, non-Fermi liquids, spin liquids, quantum criticality, charge density waves, metal-insulator transitions
Superconductivity theory, models, experiment. Superflow in helium
Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
Covers models of computation, complexity classes, structural complexity, complexity tradeoffs, upper and lower bounds. Roughly includes material in ACM Subject Classes F.1 (computation by abstract devices), F.2.3 (tradeoffs among complexity measures), and F.4.3 (formal languages), although some material in formal languages may be more appropriate for Logic in Computer Science. Some material in F.2.1 and F.2.2, may also be appropriate here, but is more likely to have Data Structures and Algorithms as the primary subject area.
Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
Roughly includes material in ACM Subject Classes I.3.5 and F.2.2.
Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.
Covers all areas of cryptography and security including authentication, public key cryptosytems, proof-carrying code, etc. Roughly includes material in ACM Subject Classes D.4.6 and E.3.
Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
Covers database management, datamining, and data processing. Roughly includes material in ACM Subject Classes E.2, E.5, H.0, H.2, and J.1.
Covers fault-tolerance, distributed algorithms, stabilility, parallel computation, and cluster computing. Roughly includes material in ACM Subject Classes C.1.2, C.1.4, C.2.4, D.1.3, D.4.5, D.4.7, E.1.
Covers combinatorics, graph theory, applications of probability. Roughly includes material in ACM Subject Classes G.2 and G.3.
Covers data structures and analysis of algorithms. Roughly includes material in ACM Subject Classes E.1, E.2, F.2.1, and F.2.2.
Covers approaches to information processing (computing, communication, sensing) and bio-chemical analysis based on alternatives to silicon CMOS-based technologies, such as nanoscale electronic, photonic, spin-based, superconducting, mechanical, bio-chemical and quantum technologies (this list is not exclusive). Topics of interest include (1) building blocks for emerging technologies, their scalability and adoption in larger systems, including integration with traditional technologies, (2) modeling, design and optimization of novel devices and systems, (3) models of computation, algorithm design and programming for emerging technologies.
Covers automata theory, formal language theory, grammars, and combinatorics on words. This roughly corresponds to ACM Subject Classes F.1.1, and F.4.3. Papers dealing with computational complexity should go to cs.CC; papers dealing with logic should go to cs.LO.
Covers all aspects of computer graphics. Roughly includes material in all of ACM Subject Class I.3, except that I.3.5 is is likely to have Computational Geometry as the primary subject area.
Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
Covers human factors, user interfaces, and collaborative computing. Roughly includes material in ACM Subject Classes H.1.2 and all of H.5, except for H.5.1, which is more likely to have Multimedia as the primary subject area.
Covers indexing, dictionaries, retrieval, content and analysis. Roughly includes material in ACM Subject Classes H.3.0, H.3.1, H.3.2, H.3.3, and H.3.4.
Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.
Covers all aspects of logic in computer science, including finite model theory, logics of programs, modal logic, and program verification. Programming language semantics should have Programming Languages as the primary subject area. Roughly includes material in ACM Subject Classes D.2.4, F.3.1, F.4.0, F.4.1, and F.4.2; some material in F.4.3 (formal languages) may also be appropriate here, although Computational Complexity is typically the more appropriate subject area.
Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
Roughly includes material in ACM Subject Class G.4.
cs.NA is an alias for math.NA. Roughly includes material in ACM Subject Class G.1.
Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
Covers performance measurement and evaluation, queueing, and simulation. Roughly includes material in ACM Subject Classes D.4.8 and K.6.2.
Covers programming language semantics, language features, programming approaches (such as object-oriented programming, functional programming, logic programming). Also includes material on compilers oriented towards programming languages; other material on compilers may be more appropriate in Architecture (AR). Roughly includes material in ACM Subject Classes D.1 and D.3.
Roughly includes material in ACM Subject Class I.2.9.
Roughly includes material in ACM Subject Class I.1.
Covers design tools, software metrics, testing and debugging, programming environments, etc. Roughly includes material in all of ACM Subject Classes D.2, except that D.2.4 (program verification) should probably have Logics in Computer Science as the primary subject area.
Covers the design, analysis, and modeling of social and information networks, including their applications for on-line information access, communication, and interaction, and their roles as datasets in the exploration of questions in these and other domains, including connections to the social and biological sciences. Analysis and modeling of such networks includes topics in ACM Subject classes F.2, G.2, G.3, H.2, and I.2; applications in computing include topics in H.3, H.4, and H.5; and applications at the interface of computing and other disciplines include topics in J.1–J.7. Papers on computer communication systems and network protocols (e.g. TCP/IP) are generally a closer fit to the Networking and Internet Architecture (cs.NI) category.
cs.SY is an alias for eess.SY. This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.
Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term “signal” includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
Results from high-energy/particle physics experiments and prospects for future experimental results, including tests of the standard model, measurements of standard model parameters, searches for physics beyond the standard model, and astroparticle physics experimental results. Does not include detectors and instrumentation nor analysis methods to conduct experiments.
Theoretical particle physics and its interrelation with experiment. Prediction of particle physics observables: models, effective field theories, calculation techniques. Particle physics: analysis of theory through experimental results.
Formal aspects of quantum field theory. String theory, supersymmetry and supergravity.
Commutative rings, modules, ideals, homological algebra, computational aspects, invariant theory, connections to algebraic geometry and combinatorics
Algebraic varieties, stacks, sheaves, schemes, moduli spaces, complex geometry, quantum cohomology
Existence and uniqueness, boundary conditions, linear and non-linear operators, stability, soliton theory, integrable PDE’s, conservation laws, qualitative dynamics
Homotopy theory, homological algebra, algebraic treatments of manifolds
Special functions, orthogonal polynomials, harmonic analysis, ODE’s, differential relations, calculus of variations, approximations, expansions, asymptotics
Discrete mathematics, graph theory, enumeration, combinatorial optimization, Ramsey theory, combinatorial game theory
Complex, contact, Riemannian, pseudo-Riemannian and Finsler geometry, relativity, gauge theory, global analysis
Dynamics of differential equations and flows, mechanics, classical few-body problems, iterations, complex dynamics, delayed differential equations
Banach spaces, function spaces, real functions, integral transforms, theory of distributions, measure theory
Mathematical material of general interest, topics not covered elsewhere
Finite groups, topological groups, representation theory, cohomology, classification and structure
Logic, set theory, point-set topology, formal mathematics
Euclidean, hyperbolic, discrete, convex, coarse geometry, comparisons in Riemannian geometry, symmetric spaces
Numerical algorithms for problems in analysis and algebra, scientific computation
Prime numbers, diophantine equations, analytic number theory, algebraic number theory, arithmetic geometry, Galois theory
Algebras of operators on Hilbert space, C^*-algebras, von Neumann algebras, non-commutative geometry
Operations research, linear programming, control theory, systems theory, optimal control, game theory
Articles in this category focus on areas of research that illustrate the application of mathematics to problems in physics, develop mathematical methods for such applications, or provide mathematically rigorous formulations of existing physical theories. Submissions to math-ph should be of interest to both physically oriented mathematicians and mathematically oriented physicists; submissions which are primarily of interest to theoretical physicists or to mathematicians should probably be directed to the respective physics/math categories
Theory and applications of probability and stochastic processes, e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
Linear representations of algebras and groups, Lie theory, associative algebras, multilinear algebra
Schrodinger operators, operators on manifolds, general differential operators, numerical studies, integral operators, discrete models, resonances, non-self-adjoint operators, random operators/matrices
Applied, computational and theoretical statistics, e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
Dynamical systems, chaos, quantum chaos, topological dynamics, cycle expansions, turbulence, propagation
Results from experimental nuclear physics including the areas of fundamental interactions, measurements at low- and medium-energy, as well as relativistic heavy-ion collisions. Does not include: detectors and instrumentation nor analysis methods to conduct experiments; descriptions of experimental programs (present or future); comments on published results.
Theory of nuclear structure covering wide area from models of hadron structure to neutron stars. Nuclear equation of states at different external conditions. Theory of nuclear reactions including heavy-ion reactions at low and high energies. It does not include problems of data analysis, physics of nuclear reactors, problems of safety, reactor construction
Accelerator theory and simulation. Accelerator technology. Accelerator experiments. Beam Physics. Accelerator design and optimization. Advanced accelerator concepts. Radiation sources including synchrotron light sources and free electron lasers. Applications of accelerators.
Atmospheric and oceanic physics and physical chemistry, biogeophysics, and climate science
Applications of physics to new technology, including electronic devices, optics, photonics, microwaves, spintronics, advanced materials, metamaterials, nanotechnology, and energy sciences.
Geometric, electronic, optical, chemical, magnetic properties, shell structure, phase transitions, optical spectroscopy, mass spectrometry, photoelectron spectroscopy, ionization potential, electron affinity, interaction with intense light pulses, electron diffraction, light scattering, ab initio calculations, DFT theory, fragmentation, Coulomb explosion, hydrodynamic expansion.
Atomic and molecular structure, spectra, collisions, and data. Atoms and molecules in external fields. Molecular dynamics and coherent and optical control. Cold atoms and molecules. Cold collisions. Optical lattices.
Molecular biophysics, cellular biophysics, neurological biophysics, membrane biophysics, single-molecule biophysics, ecological biophysics, quantum phenomena in biological systems (quantum biophysics), theoretical biophysics, molecular dynamics/modeling and simulation, game theory, biomechanics, bioinformatics, microorganisms, virology, evolution, biophysical methods.
Experimental, computational, and theoretical physics of atoms, molecules, and clusters - Classical and quantum description of states, processes, and dynamics; spectroscopy, electronic structure, conformations, reactions, interactions, and phases. Chemical thermodynamics. Disperse systems. High pressure chemistry. Solid state chemistry. Surface and interface chemistry.
Newtonian and relativistic dynamics; many particle systems; planetary motions; chaos in classical dynamics. Maxwell’s equations and dynamics of charged systems and electromagnetic forces in materials. Vibrating systems such as membranes and cantilevers; optomechanics. Classical waves, including acoustics and elasticity; physics of music and musical instruments. Classical thermodynamics and heat flow problems.
All aspects of computational science applied to physics.
Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
Turbulence, instabilities, incompressible/compressible flows, reacting flows. Aero/hydrodynamics, fluid-structure interactions, acoustics. Biological fluid dynamics, micro/nanofluidics, interfacial phenomena. Complex fluids, suspensions and granular flows, porous media flows. Geophysical flows, thermoconvective and stratified flows. Mathematical and computational methods for fluid dynamics, fluid flow models, experimental techniques.
Atmospheric physics. Biogeosciences. Computational geophysics. Geographic location. Geoinformatics. Geophysical techniques. Hydrospheric geophysics. Magnetospheric physics. Mathematical geophysics. Planetology. Solar system. Solid earth geophysics. Space plasma physics. Mineral physics. High pressure physics.
History and philosophy of all branches of physics, astrophysics, and cosmology, including appreciations of physicists.
Instrumentation and Detectors for research in natural science, including optical, molecular, atomic, nuclear and particle physics instrumentation and the associated electronics, services, infrastructure and control equipment.
Radiation therapy. Radiation dosimetry. Biomedical imaging modelling. Reconstruction, processing, and analysis. Biomedical system modelling and analysis. Health physics. New imaging or therapy modalities.
Adaptive optics. Astronomical optics. Atmospheric optics. Biomedical optics. Cardinal points. Collimation. Doppler effect. Fiber optics. Fourier optics. Geometrical optics (Gradient index optics. Holography. Infrared optics. Integrated optics. Laser applications. Laser optical systems. Lasers. Light amplification. Light diffraction. Luminescence. Microoptics. Nano optics. Ocean optics. Optical computing. Optical devices. Optical imaging. Optical materials. Optical metrology. Optical microscopy. Optical properties. Optical signal processing. Optical testing techniques. Optical wave propagation. Paraxial optics. Photoabsorption. Photoexcitations. Physical optics. Physiological optics. Quantum optics. Segmented optics. Spectra. Statistical optics. Surface optics. Ultrafast optics. Wave optics. X-ray optics.
Fundamental plasma physics. Magnetically Confined Plasmas (includes magnetic fusion energy research). High Energy Density Plasmas (inertial confinement plasmas, laser-plasma interactions). Ionospheric, Heliophysical, and Astrophysical plasmas (includes sun and solar system plasmas). Lasers, Accelerators, and Radiation Generation. Low temperature plasmas and plasma applications (include dusty plasmas, semiconductor etching, plasma-based nanotechnology, medical applications). Plasma Diagnostics, Engineering and Enabling Technologies (includes fusion reactor design, heating systems, diagnostics, experimental techniques)
Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
DNA, RNA, proteins, lipids, etc.; molecular structures and folding kinetics; molecular interactions; single-molecule manipulation.
DNA sequencing and assembly; gene and motif finding; RNA editing and alternative splicing; genomic structure and processes (replication, transcription, methylation, etc); mutational processes.
Population dynamics, spatio-temporal and epidemiological models, dynamic speciation, co-evolution, biodiversity, foodwebs, aging; molecular evolution and phylogeny; directed evolution; origin of life
All experimental, numerical, statistical and mathematical contributions of value to biology
Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
Description coming soon
Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
Algorithms, Simulation, Visualization
Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
Covers machine learning papers (supervised, unsupervised, semi-supervised learning, graphical models, reinforcement learning, bandits, high dimensional inference, etc.) with a statistical or theoretical grounding
stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.