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How to acknowledge hypercomputation?
, 2007
"... We discuss the question of how to operationally validate whether or not a “hypercomputer” performs better than the known discrete computational models. ..."
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We discuss the question of how to operationally validate whether or not a “hypercomputer” performs better than the known discrete computational models.
Formal Proof: Reconciling Correctness and Understanding
, 2009
"... Hilbert’s concept of formal proof is an ideal of rigour for mathematics which has important applications in mathematical logic, but seems irrelevant for the practice of mathematics. The advent, in the last twenty years, of proof assistants was followed by an impressive record of deep mathematical th ..."
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Hilbert’s concept of formal proof is an ideal of rigour for mathematics which has important applications in mathematical logic, but seems irrelevant for the practice of mathematics. The advent, in the last twenty years, of proof assistants was followed by an impressive record of deep mathematical theorems formally proved. Formal proof is practically achievable. With formal proof, correctness reaches a standard that no penandpaper proof can match, but an essential component of mathematics — the insight and understanding — seems to be in short supply. So, what makes a proof understandable? To answer this question we first suggest a list of symptoms of understanding. We then propose a vision of an environment in which users can write and check formal proofs as well as query them with reference to the symptoms of understanding. In this way, the environment reconciles the main features of proof: correctness and understanding.
and
, 2007
"... We discuss the question of how to operationally validate whether or not a “hypercomputer ” performs better than the known discrete computational models. 1 ..."
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We discuss the question of how to operationally validate whether or not a “hypercomputer ” performs better than the known discrete computational models. 1
A ProgramSize Complexity Measure for Mathematical Problems and Conjectures
"... Abstract. Cristian Calude et al. in [5] have recently introduced the idea of measuring the degree of difficulty of a mathematical problem (even those still given as conjectures) by the length of a program to verify or refute the statement. The method to evaluate and compare problems, in some objecti ..."
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Abstract. Cristian Calude et al. in [5] have recently introduced the idea of measuring the degree of difficulty of a mathematical problem (even those still given as conjectures) by the length of a program to verify or refute the statement. The method to evaluate and compare problems, in some objective way, will be discussed in this note. For the practitioner, wishing to apply this method using a standard universal register machine language, we provide (for the first time) some “small ” core subroutines or library for dealing with array data structures. These can be used to ease the development of full programs to check mathematical problems that require more than a predetermined finite number of variables. 1
Omega and the time evolution of the nbody problem
, 2007
"... The series solution of the behavior of a finite number of physical bodies and Chaitin’s Omega number share quasialgorithmic expressions; yet both lack a computable radius of convergence. ..."
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The series solution of the behavior of a finite number of physical bodies and Chaitin’s Omega number share quasialgorithmic expressions; yet both lack a computable radius of convergence.
Physical unknowables
, 2008
"... Different types of physical unknowables are discussed. Provable unknowables are derived from reduction to problems which are known to be recursively unsolvable. Recent series solutions to the nbody problem and related to it, chaotic systems, may have no computable radius of convergence. Quantum unk ..."
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Different types of physical unknowables are discussed. Provable unknowables are derived from reduction to problems which are known to be recursively unsolvable. Recent series solutions to the nbody problem and related to it, chaotic systems, may have no computable radius of convergence. Quantum unknowables include the random occurrence of single events, complementarity and value indefiniteness.
Combinatorial Spaces And Order Topologies Philon Nguyen
"... Abstract. An archetypal problem discussed in computer science is the problem of searching for a given number in a given set of numbers. Other than sequential search, the classic solution is to sort the list of numbers and then apply binary search. The binary search problem has a complexity of O(lo ..."
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Abstract. An archetypal problem discussed in computer science is the problem of searching for a given number in a given set of numbers. Other than sequential search, the classic solution is to sort the list of numbers and then apply binary search. The binary search problem has a complexity of O(logN) for a list of N numbers while the sorting problem cannot be better than O(N) on any sequential computer following the usual assumptions. Whenever the problem of deciding partial order can be done in O(1), a variation of the problem on some bounded list of numbers is to apply binary search without resorting to sort. The overall complexity of the problem is then O(logR) for some radius R. The following upperbound for finite encodings is shown: O(logX ∞ log log N) Also, the topology of orderings can provide efficient algorithms for search problems in combinatorial spaces. The main characteristic of those spaces is that they have typical space complexities of O(2N), O(N!) and O(NN). The factorial case describes an order topology that can be illustrated using the combinatorial polytope. When a known order topology can be combined to a given formulation of a search problem, the resulting search problem has a polylogarithmic complexity. This logarithmic complexity can then become useful in combinatorial search by providing a logarithmic breakdown. These algorithms can be termed as the class of search algorithms that do not require read and are equivalent to the class of logarithmically recursive functions. Also, the notion of order invariance is discussed. 1. Computable Structures A few terminological remarks can be made on the algebra of computable structures. Remark 1.1. A computable space is defined using the distinguishability problem. Remark 1.2. A computable space is said to be complete if it can represent a Turingcomplete space. Furthermore, the following can be noted: Remark 1.3. The equality operator is defined using the cut metric of Equation 3.0.11. This is denoted = N