The complexity and entropy of Turing machines

2002 ◽  
Author(s):  
P.A. Dufort ◽  
C.J. Lumsden
Keyword(s):  
Turing Machines

Some Assumptions about Problem Solving Representation in Turing’s Model of Intelligence

1970 ◽  
Vol 4 (2) ◽  
pp. 136-142 ◽  
Author(s):  
Raymundo Morado ◽  
Francisco Hernández-Quiroz
Keyword(s):  
Problem Solving ◽  
Computational Models ◽  
Turing Machines

Turing machines as a model of intelligence can be motivated under some assumptions, both mathematical and philosophical. Some of these are about the possibility, the necessity, and the limits of representing problem solving by mechanical means. The assumptions about representation that we consider in this paper are related to information representability and availability, processing as solving, nonessentiality of complexity issues, and finiteness, discreteness and sequentiality of the representation. We discuss these assumptions and particularly something that might happen if they were to be rejected or weakened. Tinkering with these assumptions sheds light on the import of alternative computational models.

The Essence of Quantum Computing

2018 ◽  
Author(s):  
Rajendra K. Bera
Keyword(s):  
Hilbert Space ◽  
Quantum Computing ◽  
Quantum Physics ◽  
Quantum Algorithms ◽  
Quantum Computers ◽  
Turing Machines ◽  
Classical Physics ◽  
Core Set ◽  
The World ◽  
Subordinate Role

It now appears that quantum computers are poised to enter the world of computing and establish its dominance, especially, in the cloud. Turing machines (classical computers) tied to the laws of classical physics will not vanish from our lives but begin to play a subordinate role to quantum computers tied to the enigmatic laws of quantum physics that deal with such non-intuitive phenomena as superposition, entanglement, collapse of the wave function, and teleportation, all occurring in Hilbert space. The aim of this 3-part paper is to introduce the readers to a core set of quantum algorithms based on the postulates of quantum mechanics, and reveal the amazing power of quantum computing.

Modeling Multitape Minsky and Turing Machines by Three-Tape Minsky Machines

2020 ◽  
Vol 46 (6) ◽  
pp. 428-432
Author(s):  
S. S. Marchenkov ◽  
S. D. Makeev
Keyword(s):  
Turing Machines

scholarly journals Turing machines with few accepting computations and low sets for PP

1992 ◽  
Vol 44 (2) ◽  
pp. 272-286 ◽  
Author(s):  
Johannes Kobler ◽  
Uwe Schïng ◽  
Seinosuke Toda ◽  
Jacobo Torán
Keyword(s):  
Turing Machines

scholarly journals Finite representability of semigroups with demonic refinement

2021 ◽  
Vol 82 (2) ◽  
Author(s):  
Robin Hirsch ◽  
Jaš Šemrl
Keyword(s):  
Partial Order ◽  
Turing Machines ◽  
Binary Relations ◽  
Finite Representation ◽  
First Order ◽  
Finite Structures ◽  
Finite Base ◽  
Finite Set ◽  
Finite Representability ◽  
Representation Class

AbstractThe motivation for using demonic calculus for binary relations stems from the behaviour of demonic turing machines, when modelled relationally. Relational composition (; ) models sequential runs of two programs and demonic refinement ($$\sqsubseteq $$ ⊑ ) arises from the partial order given by modeling demonic choice ($$\sqcup $$ ⊔ ) of programs (see below for the formal relational definitions). We prove that the class $$R(\sqsubseteq , ;)$$ R ( ⊑ , ; ) of abstract $$(\le , \circ )$$ ( ≤ , ∘ ) structures isomorphic to a set of binary relations ordered by demonic refinement with composition cannot be axiomatised by any finite set of first-order $$(\le , \circ )$$ ( ≤ , ∘ ) formulas. We provide a fairly simple, infinite, recursive axiomatisation that defines $$R(\sqsubseteq , ;)$$ R ( ⊑ , ; ) . We prove that a finite representable $$(\le , \circ )$$ ( ≤ , ∘ ) structure has a representation over a finite base. This appears to be the first example of a signature for binary relations with composition where the representation class is non-finitely axiomatisable, but where the finite representation property holds for finite structures.

An instruction set for reversible Turing machines

2021 ◽  
Vol 58 (4) ◽  
pp. 377-396
Author(s):  
Kenichi Morita
Keyword(s):  
Turing Machines ◽  
Instruction Set
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