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Search · four archives
21 papers · ranked by Valyu relevance
Aaron Karper
| 1 | Introduction | | 3 | | --- | --- | --- | --- | | | | 1.0.1 What is a programming language? | 4 | | | 1.1 | The FOR language | 6 | | | | 1.1.1 The Elements | 6 | | | | 1.1.2 Coding FOR programs | 7 | | | | 1.1.3 FOR computability | 9 | | | | 1.1.4 The FOR in real programming languages | 10 | | | | 1.1.5 The FOR in…
Erin Kathryn Carmody
This paper analyzes infinitary nondeterministic computability theory. The main result is D ̸= ND ∩ coND where D is the class of sets decidable by infinite time Turing machines and ND is the class of sets recognizable by a nondeterministic infinite time Turing machine. Nondeterministic infinite time Turing machines are…
Elizabeth A Stoll
In cortical neurons, spontaneous membrane potential fluctuations affect the likelihood of firing an action potential. Yet despite retaining sensitivity to random electrical noise in gating signaling outcomes, these cells achieve highly accurate computations with extraordinary energy efficiency. A new approach models…
Andrew Currin, Konstantin Korovin, Maria Ababi, Katherine Roper + 3 more
'Douglas B. Kell' 'Philip J. Day' 'Ross D. King'] The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science…
Elizabeth A Stoll
Cortical neurons allow random electrical noise to contribute to the likelihood of firing a signal. Previous approaches have involved statistically modeling signaling outcomes in neuronal populations, or modeling the dynamical relationship between membrane potential, ion channel activation, and ion conductance in…
Elizabeth A Stoll
It has historically proven difficult to explain the relationship between neural activity and representative information content. A new approach focuses on the unique properties of cortical neurons, which allow both upstream signals and random electrical noise to affect the likelihood of reaching action potential…
Elizabeth A Stoll
Neuronal populations in the cerebral cortex engage in probabilistic coding, effectively encoding the state of the surrounding environment with high accuracy and extraordinary energy efficiency. A new approach models the inherently probabilistic nature of cortical neuron signaling outcomes as a thermodynamic process of…
Gilles Dowek
The physical Church-Turing thesis, if it holds, suggests that the laws of nature can be expressed, not only in the language of mathematics, but also in an algorithmic language. Gandy's argument, that support the physical Church-Turing thesis, even suggests that these algorithms may operate on the elements of a…
Stephen Wolfram
We give a modern computational introduction to the S,K combinators invented by Moses Schönfinkel in 1920, and present a variety of new results and ideas about combinators.We explore the spectrum of behavior obtained with small combinator expressions, showing a variety of approaches to analysis and visualization.We…
Yuri Gurevich
The modern notion of algorithm was elucidated in the 1930s–1950s. It was axiomatized a quarter of a century ago as the notion of "sequential algorithm" or "classical algorithm"; we prefer to call it "basic algorithm" now. The axiomatization was used to show that for every basic algorithm there is a behaviorally…
W. Richard Stark
The cellular automata model was described by John von Neumann and his friends in the 1950s as a representation of information processing in multicellular tissue. With crystalline arrays of cells and synchronous activity, it missed the mark (Stark and Hughes, BioSystems 55:107-117, [22]). Recently, amorphous computing…
Edward A. Lee
“Rationality” in Simon's “bounded rationality” is the principle that humans make decisions on the basis of step-by-step (algorithmic) reasoning using systematic rules of logic to maximize utility. “Bounded rationality” is the observation that the ability of a human brain to handle algorithmic complexity and large…
Michael P. Frank, Karpur Shukla, Neal G. Anderson
The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible digital paradigm. However, to date, the essential rationale for, and analysis of, classical…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Aldo Solís, Jorge G. Hirsch
Randomness plays a central rol in the quantum mechanical description of our interactions. We review the relationship between the violation of Bell inequalities, non signaling and randomness. We discuss the challenge in defining a random string, and show that algorithmic information theory provides a necessary condition…
Clare Horsman, Susan Stepney, Rob C. Wagner, Viv Kendon
Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or…
Gustavo Deco, Yonatan Sanz Perl, Jakub Vohryzek, Andrea Luppi + 1 more
The perhaps most important unsolved problem in neuroscience is how the brain survives in a complex world by performing a rich repertoire of computation on a minimal energy budget. The brain is much better at adapting to the multiplicity of stimuli and outcomes than current generations of computers, artificial neural…
Marta Dueñas-Díez, Juan Pérez-Mercader
Computing with molecules is at the center of complex natural phenomena, where the information contained in ordered sequences of molecules is used to implement functionalities of synthesized materials or to interpret the environment, as in Biology. This uses large macromolecules and the hindsight of billions of years of…
Authors not listed
Strong coupling and environmental memory render many open quantum systems intractable to classical computation. To overcome this barrier, we present a variational quantum algorithm capable of solving generalized form time-local quantum master equations directly on Noisy Intermediate-Scale Quantum (NISQ) processors. Our…
Authors not listed
Nonadiabatic dynamics simulations complement time-resolved experiments by revealing ultrafast excited-states mechanistic information in photochemical reactions. Understanding the relaxation mechanisms of photo-excited molecules finds application in energy, material, and medicinal research. However, with substantial…
Authors not listed
We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxide are treated explicitly, so both mass and charge are balanced. We…