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Encyclopedia > L (complexity)

In computational complexity theory, L is the complexity class containing decision problems which can be solved by a deterministic Turing machine using a logarithmic amount of memory space. Intuitively, logarithmic space is enough space to hold a constant number of pointers into the input.


A generalization of L is NL, which is the class of languages decidable in logarithmic space on a nondeterministic Turing machine. We then trivially have L \subseteq NL. Also, a decider using O(log n) space cannot use more than 2O(log n)=nO(1) time, because this is the total number of possible configurations; thus, L \subseteq P.


Every problem in L is complete under log-space reductions; since this is useless, weaker reductions are defined which allow identification of stronger complete problems in L, but there is no generally accepted definition of L-complete.


Important open problems include whether L = P, and whether L = NL.


The related class of function problems is FL. FL is often used to define logspace reductions.


A breakthrough October 2004 paper by Omer Reingold showed that USTCON, the problem of whether there exists a path between two vertices in a given undirected graph, is in L, establishing that L = SL, since USTCON is SL-complete.


One consequence of this is a simple logical characterization of L: it contains precisely those languages expressible in first order logic with an added commutative transitive closure operator.


References

  • Papadimitriou, Computational Complexity Theory.
  • Undirected ST-connectivity in Log-Space (http://www.wisdom.weizmann.ac.il/~reingold/publications/sl.ps). Omer Reingold. Electronic Colloquium on Computational Complexity. No. 94.


Important complexity classes (more)
P | NP | Co-NP | NP-C | Co-NP-C | NP-hard | UP | #P | #P-C | L | NC | P-C
PSPACE | PSPACE-C | EXPTIME | EXPSPACE | BQP | BPP | RP | ZPP | PCP | IP | PH

  Results from FactBites:
 
Complexity Society (206 words)
It is a community that uses complexity science to rethink and reinterpret all aspects of the world in which we live and work.
The society objectives are to promote the theory of complexity in education, government, the health service and business as well as the beneficial application of complexity in a wide variety of social, economic, scientific and technological contexts such as sources of competitive advantage, business clusters and knowledge management.
Complexity includes ideas such as complex adaptive systems, self-organisation, co-evolution, agent based computer models, chaos, networks, emergence and fractals.
  More results at FactBites »

 

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