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We outline the construction of a molecular system that could, in principle, implement a thermodynamically reversible Universal Turing Machine (UTM). By proposing a concrete-albeit idealised-design and operational protocol, we reveal…

Statistical Mechanics · Physics 2021-02-09 Rory A. Brittain , Nick S. Jones , Thomas E. Ouldridge

This study focuses on finite-sample inference on the non-linear Bures-Wasserstein manifold and introduces a generalized bootstrap procedure for estimating Bures-Wasserstein barycenters. We provide non-asymptotic statistical guarantees for…

Statistics Theory · Mathematics 2024-11-26 Alexey Kroshnin , Vladimir Spokoiny , Alexandra Suvorikova

In this essay, I argue that explicit ethical machines, whose moral principles are inferred through a bottom-up approach, are unable to replicate human-like moral reasoning and cannot be considered moral agents. By utilizing Alan Turing's…

Computers and Society · Computer Science 2024-07-25 Massimo Passamonti

Asymptotic statistical theory for estimating functions is reviewed in a generality suitable for stochastic processes. Conditions concerning existence of a consistent estimator, uniqueness, rate of convergence, and the asymptotic…

Statistics Theory · Mathematics 2018-09-06 Jean Jacod , Michael Sørensen

The diffusion-driven Turing instability is a potential mechanism for spatial pattern formation in numerous biological and chemical systems. However, engineering these patterns and demonstrating that they are produced by this mechanism is…

Biological Physics · Physics 2025-12-02 Antonio Matas-Gil , Robert G. Endres

Recent breakthroughs in AI capability have been attributed to increasingly sophisticated architectures and alignment techniques, but a simpler principle may explain these advances: memory makes computation universal. Memory enables…

Machine Learning · Computer Science 2024-12-24 Erik Garrison

This manuscript aims to illustrate a quantum-classical dissipative theory (suited to be converted to effective algorithms for numerical simulations) within the long-term project of studying molecular processes in the brain. Other…

Neurons and Cognition · Quantitative Biology 2025-03-04 Alessandro Sergi , Antonino Messina , Rosalba Saija , Gabriella Martino , Maria Teresa Caccamo , Min-Fang Kuo , Michael A. Nitsche

Mathematical models implemented on a computer have become the driving force behind the acceleration of the cycle of scientific processes. This is because computer models are typically much faster and economical to run than physical…

Computation · Statistics 2021-07-05 Vojtech Kejzlar , Mookyong Son , Shrijita Bhattacharya , Tapabrata Maiti

This paper provides a new and more direct proof of the assertion that a Turing computable function of the natural numbers is primitive recursive if and only if the time complexity of the corresponding Turing machine is bounded by a…

Formal Languages and Automata Theory · Computer Science 2025-10-22 Daniel G. Schwartz

This paper examines the claim that cellular automata (CA) belonging to Class III (in Wolfram's classification) are capable of (Turing universal) computation. We explore some chaotic CA (believed to belong to Class III) reported over the…

Cellular Automata and Lattice Gases · Physics 2013-04-05 Genaro J. Martinez , Juan C. Seck-Tuoh-Mora , Hector Zenil

Computational complexity theory contains a corpus of theorems and conjectures regarding the time a Turing machine will need to solve certain types of problems as a function of the input size. Nature {\em need not} be a Turing machine and,…

Quantum Physics · Physics 2015-05-20 Javier Rodriguez-Laguna , Silvia N. Santalla

We explore the relationship between Turing completeness and topological entropy of dynamical systems. We first prove that a natural class of Turing machines that we call "branching Turing machines" (which includes most of the known examples…

Dynamical Systems · Mathematics 2026-04-10 Renzo Bruera , Robert Cardona , Eva Miranda , Daniel Peralta-Salas , Ville Salo

The standard approach to analyzing the asymptotic complexity of probabilistic programs is based on studying the asymptotic growth of certain expected values (such as the expected termination time) for increasing input size. We argue that…

Formal Languages and Automata Theory · Computer Science 2023-07-13 Michal Ajdarów , Antonín Kučera

While deep neural networks have become the go-to approach in computer vision, the vast majority of these models fail to properly capture the uncertainty inherent in their predictions. Estimating this predictive uncertainty can be crucial,…

Machine Learning · Computer Science 2020-04-08 Fredrik K. Gustafsson , Martin Danelljan , Thomas B. Schön

We introduce the zeta number, natural halting probability and natural complexity of a Turing machine and we relate them to Chaitin's Omega number, halting probability, and program-size complexity. A classification of Turing machines…

Computational Complexity · Computer Science 2007-05-23 Cristian S. Calude , Michael A. Stay

Human behavior modeling is important for the design and implementation of human-automation interactive control systems. In this context, human behavior refers to a human's control input to systems. We propose a novel method for human…

Robotics · Computer Science 2024-04-24 Sooyung Byeon , Dawei Sun , Inseok Hwang

The Turing Machine is the paradigmatic case of computing machines, but there are others such as analogical, connectionist, quantum and diverse forms of unconventional computing, each based on a particular intuition of the phenomenon of…

Artificial Intelligence · Computer Science 2023-10-10 Luis A. Pineda

This paper constructively proves the existence of an effective procedure generating a computable (total) function that is not contained in any given effectively enumerable set of such functions. The proof implies the existence of machines…

Artificial Intelligence · Computer Science 2010-05-05 Kurt Ammon

In 1950, Alan Turing proposed replacing the question "Can machines think?" with a behavioral test: if a machine's outputs are indistinguishable from those of a thinking being, the question of whether it truly thinks can be set aside. This…

Artificial Intelligence · Computer Science 2026-04-28 Amir Konigsberg

Inverse optimal control can be used to characterize behavior in sequential decision-making tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce…

Machine Learning · Computer Science 2023-10-31 Dominik Straub , Matthias Schultheis , Heinz Koeppl , Constantin A. Rothkopf