In computational complexity theory, '''''' is the set of all decision problems solvable by a deterministic Turing machine in exponential space, i.e., in O(2^{p(n)}) space, where p(n) is a polynomial function of n. Some authors restrict p(n) to be a linear function, but most authors instead call the resulting class . If we use a nondeterministic machine instead, we get the class , which is equal to by Savitch's theorem.
In computational complexity theory, '''''' is the set of all decision problems solvable by a deterministic Turing machine in exponential space, i.e., in O(2^{p(n)}) space, where p(n) is a polynomial function of n. Some authors restrict p(n) to be a linear function, but most authors instead call the resulting class . If we use a nondeterministic machine instead, we get the class , which is equal to by Savitch's theorem.
A decision problem is if it is in , and every problem in has a polynomial-time many-one reduction to it. In other words, there is a polynomial-time algorithm that transforms instances of one to instances of the other with the same answer. problems might be thought of as the hardest problems in .
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).