19,068 research outputs found
On Determinism Versus Non-Determinism And Related Problems
We show that, for multi-tape Turing machines, non-deterministic linear time is more deterministic Turing machines (that receive their input on their work tape) require time Q(n2) to powerful than deterministic linear time. We also recognize non-palindromes of length n (it is easy to discuss the prospects for extending this result to see that time O(n log n) is. sufficient for a more general Turing machines. non-deterministic machine). 1. Introductio
Reversibility and Adiabatic Computation: Trading Time and Space for Energy
Future miniaturization and mobilization of computing devices requires energy
parsimonious `adiabatic' computation. This is contingent on logical
reversibility of computation. An example is the idea of quantum computations
which are reversible except for the irreversible observation steps. We propose
to study quantitatively the exchange of computational resources like time and
space for irreversibility in computations. Reversible simulations of
irreversible computations are memory intensive. Such (polynomial time)
simulations are analysed here in terms of `reversible' pebble games. We show
that Bennett's pebbling strategy uses least additional space for the greatest
number of simulated steps. We derive a trade-off for storage space versus
irreversible erasure. Next we consider reversible computation itself. An
alternative proof is provided for the precise expression of the ultimate
irreversibility cost of an otherwise reversible computation without
restrictions on time and space use. A time-irreversibility trade-off hierarchy
in the exponential time region is exhibited. Finally, extreme
time-irreversibility trade-offs for reversible computations in the thoroughly
unrealistic range of computable versus noncomputable time-bounds are given.Comment: 30 pages, Latex. Lemma 2.3 should be replaced by the slightly better
``There is a winning strategy with pebbles and erasures for
pebble games with , for all '' with appropriate
further changes (as pointed out by Wim van Dam). This and further work on
reversible simulations as in Section 2 appears in quant-ph/970300
Thermodynamics of stochastic Turing machines
In analogy to Brownian computers we explicitly show how to construct
stochastic models, which mimic the behaviour of a general purpose computer (a
Turing machine). Our models are discrete state systems obeying a Markovian
master equation, which are logically reversible and have a well-defined and
consistent thermodynamic interpretation. The resulting master equation, which
describes a simple one-step process on an enormously large state space, allows
us to thoroughly investigate the thermodynamics of computation for this
situation. Especially, in the stationary regime we can well approximate the
master equation by a simple Fokker-Planck equation in one dimension. We then
show that the entropy production rate at steady state can be made arbitrarily
small, but the total (integrated) entropy production is finite and grows
logarithmically with the number of computational steps.Comment: 13 pages incl. appendix, 3 figures and 1 table, slightly changed
version as published in PR
A Mathematical Model of Quantum Computer by Both Arithmetic and Set Theory
A practical viewpoint links reality, representation, and language to calculation by the concept of Turing (1936) machine being the mathematical model of our computers. After the Gödel incompleteness theorems (1931) or the insolvability of the so-called halting problem (Turing 1936; Church 1936) as to a classical machine of Turing, one of the simplest hypotheses is completeness to be suggested for two ones. That is consistent with the provability of completeness by means of two independent Peano arithmetics discussed in Section I.
Many modifications of Turing machines cum quantum ones are researched in Section II for the Halting problem and completeness, and the model of two independent Turing machines seems to generalize them.
Then, that pair can be postulated as the formal definition of reality therefore being complete unlike any of them standalone, remaining incomplete without its complementary counterpart. Representation is formal defined as a one-to-one mapping between the two Turing machines, and the set of all those mappings can be considered as “language” therefore including metaphors as mappings different than representation. Section III investigates that formal relation of “reality”, “representation”, and “language” modeled by (at least two) Turing machines. The independence of (two) Turing machines is interpreted by means of game theory and especially of the Nash equilibrium in Section IV.
Choice and information as the quantity of choices are involved. That approach seems to be equivalent to that based on set theory and the concept of actual infinity in mathematics and allowing of practical implementations
Observations on complete sets between linear time and polynomial time
AbstractThere is a single set that is complete for a variety of nondeterministic time complexity classes with respect to related versions of m-reducibility. This observation immediately leads to transfer results for determinism versus nondeterminism solutions. Also, an upward transfer of collapses of certain oracle hierarchies, built analogously to the polynomial-time or the linear-time hierarchies, can be shown by means of uniformly constructed sets that are complete for related levels of all these hierarchies. A similar result holds for difference hierarchies over nondeterministic complexity classes. Finally, we give an oracle set relative to which the nondeterministic classes coincide with the deterministic ones, for several sets of time bounds, and we prove that the strictness of the tape-number hierarchy for deterministic linear-time Turing machines does not relativize
Quantum Random Self-Modifiable Computation
Among the fundamental questions in computer science, at least two have a deep
impact on mathematics. What can computation compute? How many steps does a
computation require to solve an instance of the 3-SAT problem? Our work
addresses the first question, by introducing a new model called the ex-machine.
The ex-machine executes Turing machine instructions and two special types of
instructions. Quantum random instructions are physically realizable with a
quantum random number generator. Meta instructions can add new states and add
new instructions to the ex-machine. A countable set of ex-machines is
constructed, each with a finite number of states and instructions; each
ex-machine can compute a Turing incomputable language, whenever the quantum
randomness measurements behave like unbiased Bernoulli trials. In 1936, Alan
Turing posed the halting problem for Turing machines and proved that this
problem is unsolvable for Turing machines. Consider an enumeration E_a(i) =
(M_i, T_i) of all Turing machines M_i and initial tapes T_i. Does there exist
an ex-machine X that has at least one evolutionary path X --> X_1 --> X_2 --> .
. . --> X_m, so at the mth stage ex-machine X_m can correctly determine for 0
<= i <= m whether M_i's execution on tape T_i eventually halts? We demonstrate
an ex-machine Q(x) that has one such evolutionary path. The existence of this
evolutionary path suggests that David Hilbert was not misguided to propose in
1900 that mathematicians search for finite processes to help construct
mathematical proofs. Our refinement is that we cannot use a fixed computer
program that behaves according to a fixed set of mechanical rules. We must
pursue methods that exploit randomness and self-modification so that the
complexity of the program can increase as it computes.Comment: 50 pages, 3 figure
- …