119 citations · 569 across the 23 of their papers we have counts for
24 papers
Surveying structural complexity in quantum many-body systems
Whei Yeap Suen, Thomas J. Elliott, Jayne Thompson +4
Quantum many-body systems exhibit a rich and diverse range of exotic behaviours, owing to their underlying non-classical structure. These systems present a deep structure beyond th…
Causal Asymmetry in a Quantum World
Jayne Thompson, Andrew J. P. Garner, John R. Mahoney +3
Causal asymmetry is one of the great surprises in predictive modelling: the memory required to predict the future differs from the memory required to retrodict the past. There is a…
Mode-locking in advection-reaction-diffusion systems: an invariant manifold perspective
Rory A. Locke, John R. Mahoney, Kevin A. Mitchell
Fronts propagating in two-dimensional advection-reaction-diffusion (ARD) systems exhibit rich topological structure. When the underlying fluid flow is periodic in space and time, t…
Optimizing Quantum Models of Classical Channels: The reverse Holevo problem
S. Loomis, J. R. Mahoney, C. Aghamohammadi +1
Given a classical channel---a stochastic map from inputs to outputs---the input can often be transformed to an intermediate variable that is informationally smaller than the input.…
Prediction and Generation of Binary Markov Processes: Can a Finite-State Fox Catch a Markov Mouse?
J. Ruebeck, R. G. James, J. R. Mahoney +1
Understanding the generative mechanism of a natural system is a vital component of the scientific method. Here, we investigate one of the fundamental steps toward this goal by pres…
Extreme Quantum Advantage for Rare-Event Sampling
C. Aghamohammadi, S. P. Loomis, J. R. Mahoney +1
We introduce a quantum algorithm for efficient biased sampling of the rare events generated by classical memoryful stochastic processes. We show that this quantum algorithm gives a…
Trimming the Independent Fat: Sufficient Statistics, Mutual Information, and Predictability from Effective Channel States
Ryan G. James, John R. Mahoney, James P. Crutchfield
One of the most fundamental questions one can ask about a pair of random variables X and Y is the value of their mutual information. Unfortunately, this task is often stymied by th…
Extreme Quantum Advantage when Simulating Strongly Coupled Classical Systems
C. Aghamohammadi, J. R. Mahoney, J. P. Crutchfield
Classical stochastic processes can be generated by quantum simulators instead of the more standard classical ones, such as hidden Markov models. One reason for using quantum simula…
The Ambiguity of Simplicity
Cina Aghamohammadi, John R. Mahoney, James P. Crutchfield
A system's apparent simplicity depends on whether it is represented classically or quantally. This is not so surprising, as classical and quantum physics are descriptive frameworks…
A Closed-Form Shave from Occam's Quantum Razor: Exact Results for Quantum Compression
Paul M. Riechers, John R. Mahoney, Cina Aghamohammadi +1
The causal structure of a stochastic process can be more efficiently transmitted via a quantum channel than a classical one, an advantage that increases with codeword length. While…
Occam's Quantum Strop: Synchronizing and Compressing Classical Cryptic Processes via a Quantum Channel
J. R. Mahoney, C. Aghamohammadi, J. P. Crutchfield
A stochastic process's statistical complexity stands out as a fundamental property: the minimum information required to synchronize one process generator to another. How much infor…
Finite-time barriers to front propagation in two-dimensional fluid flows
John R. Mahoney, Kevin A. Mitchell
Recent theoretical and experimental investigations have demonstrated the role of certain invariant manifolds, termed burning invariant manifolds (BIMs), as one-way dynamical barrie…
Frozen reaction fronts in steady flows: a burning-invariant-manifold perspective
John R. Mahoney, John Li, Carleen Boyer +2
The dynamics of fronts, such as chemical reaction fronts, propagating in two-dimensional fluid flows can be remarkably rich and varied. For time-invariant flows, the front dynamics…
A turnstile mechanism for fronts propagating in fluid flows
John R. Mahoney, Kevin A. Mitchell
We consider the propagation of fronts in a periodically driven flowing medium. It is shown that the progress of fronts in these systems may be mediated by a turnstile mechanism aki…
Invariant manifolds and the geometry of front propagation in fluid flows
Kevin A. Mitchell, John R. Mahoney
Recent theoretical and experimental work has demonstrated the existence of one-sided, invariant barriers to the propagation of reaction-diffusion fronts in quasi-two-dimensional pe…
How Hidden are Hidden Processes? A Primer on Crypticity and Entropy Convergence
John R. Mahoney, Christopher J. Ellison, Ryan G. James +1
We investigate a stationary process's crypticity---a measure of the difference between its hidden state information and its observed information---using the causal states of comput…
Invariant barriers to reactive front propagation in fluid flows
John Mahoney, Dylan Bargteil, Mark Kingsbury +2
We present theory and experiments on the dynamics of reaction fronts in two-dimensional, vortex-dominated flows, for both time-independent and periodically driven cases. We find th…
Information Symmetries in Irreversible Processes
Christopher J. Ellison, John R. Mahoney, Ryan G. James +2
We study dynamical reversibility in stationary stochastic processes from an information theoretic perspective. Extending earlier work on the reversibility of Markov chains, we focu…
Many Roads to Synchrony: Natural Time Scales and Their Algorithms
Ryan G. James, John R. Mahoney, Christopher J. Ellison +1
We consider two important time scales---the Markov and cryptic orders---that monitor how an observer synchronizes to a finitary stochastic process. We show how to compute these ord…
Synchronization and Control in Intrinsic and Designed Computation: An Information-Theoretic Analysis of Competing Models of Stochastic Computation
James P. Crutchfield, Christopher J. Ellison, Ryan G. James +1
We adapt tools from information theory to analyze how an observer comes to synchronize with the hidden states of a finitary, stationary stochastic process. We show that synchroniza…
Information Accessibility and Cryptic Processes: Linear Combinations of Causal States
John R. Mahoney, Christopher J. Ellison, James P. Crutchfield
We show in detail how to determine the time-reversed representation of a stationary hidden stochastic process from linear combinations of its forward-time -machine causal states…
Information Accessibility and Cryptic Processes
John R. Mahoney, Christopher J. Ellison, James P. Crutchfield
We give a systematic expansion of the crypticity--a recently introduced measure of the inaccessibility of a stationary process's internal state information. This leads to a hierarc…
Prediction, Retrodiction, and The Amount of Information Stored in the Present
Christopher J. Ellison, John R. Mahoney, James P. Crutchfield
We introduce an ambidextrous view of stochastic dynamical systems, comparing their forward-time and reverse-time representations and then integrating them into a single time-symmet…
Time's Barbed Arrow: Irreversibility, Crypticity, and Stored Information
James P. Crutchfield, Christopher J. Ellison, John R. Mahoney
We show why the amount of information communicated between the past and future--the excess entropy--is not in general the amount of information stored in the present--the statistic…