Randomized Logarithmic-space (RL), sometimes called RLP (Randomized Logarithmic-space Polynomial-time), is the
complexity class
In computational complexity theory, a complexity class is a set of computational problems of related resource-based complexity. The two most commonly analyzed resources are time and memory.
In general, a complexity class is defined in terms ...
of
computational complexity theory
In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved ...
problems solvable in
logarithmic space and
polynomial time
In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by ...
with
probabilistic Turing machine
In theoretical computer science, a probabilistic Turing machine is a non-deterministic Turing machine that chooses between the available transitions at each point according to some probability distribution. As a consequence, a probabilistic Turin ...
s with
one-sided error. It is named in analogy with
RP, which is similar but has no logarithmic space restriction.
Definition
The probabilistic Turing machines in the definition of RL never accept incorrectly but are allowed to reject incorrectly less than 1/3 of the time; this is called ''one-sided error''. The constant 1/3 is arbitrary; any ''x'' with 0 < ''x'' < 1 would suffice. This error can be made 2
−''p''(''x'') times smaller for any polynomial ''p''(''x'') without using more than polynomial time or logarithmic space by running the algorithm repeatedly.
Relation to other complexity classes
Sometimes the name RL is reserved for the class of problems solvable by logarithmic-space probabilistic machines in ''unbounded'' time. However, this class can be shown to be equal to
NL using a probabilistic counter, and so is usually referred to as NL instead; this also shows that RL is contained in NL. RL is contained in
BPL, which is similar but allows two-sided error (incorrect accepts). RL contains
L, the problems solvable by
deterministic Turing machine
A Turing machine is a mathematical model of computation describing an abstract machine that manipulates symbols on a strip of tape according to a table of rules. Despite the model's simplicity, it is capable of implementing any computer algor ...
s in log space, since its definition is just more general.
Noam Nisan
Noam Nisan ( he, נעם ניסן; born June 20, 1961) is an Israeli computer scientist, a professor of computer science at the Hebrew University of Jerusalem. He is known for his research in computational complexity theory and algorithmic game t ...
showed in 1992 the weak
derandomization
A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performan ...
result that RL is contained in
SC, the class of problems solvable in polynomial time and polylogarithmic space on a deterministic Turing machine; in other words, given ''polylogarithmic'' space, a deterministic machine can simulate ''logarithmic'' space probabilistic algorithms.
It is believed that RL is equal to L, that is, that polynomial-time logspace computation can be completely derandomized; major evidence for this was presented by Reingold et al. in 2005.
[O. Reingold and L. Trevisan and S. Vadhan. Pseudorandom walks in biregular graphs and the RL vs. L problem, , 2004.] A proof of this is the holy grail of the efforts in the field of unconditional derandomization of complexity classes. A major step forward was Omer Reingold's proof that
SL is equal to L.
References
{{DEFAULTSORT:Rl (Complexity)
Probabilistic complexity classes