32 citations · 101 across the 9 of their papers we have counts for
9 papers
Exploring Predictive States via Cantor Embeddings and Wasserstein Distance
Samuel P. Loomis, James P. Crutchfield
Predictive states for stochastic processes are a nonparametric and interpretable construct with relevance across a multitude of modeling paradigms. Recent progress on the self-supe…
Topology, Convergence, and Reconstruction of Predictive States
Samuel P. Loomis, James P. Crutchfield
Predictive equivalence in discrete stochastic processes have been applied with great success to identify randomness and structure in statistical physics and chaotic dynamical syste…
Nonequilibrium Thermodynamics in Measuring Carbon Footprints: Disentangling Structure and Artifact in Input-Output Accounting
Samuel P. Loomis, Mark Cooper, James P. Crutchfield
Multiregional input-output (MRIO) tables, in conjunction with Leontief analysis, are widely-used to assess the geographical distribution of carbon emissions and the economic activi…
Thermodynamically-Efficient Local Computation and the Inefficiency of Quantum Memory Compression
Samuel P. Loomis, James P. Crutchfield
Modularity dissipation identifies how locally-implemented computation entails costs beyond those required by Landauer's bound on thermodynamic computing. We establish a general the…
Thermal Efficiency of Quantum Memory Compression
Samuel P. Loomis, James P. Crutchfield
Quantum coherence allows for reduced-memory simulators of classical processes. Using recent results in single-shot quantum thermodynamics, we derive a minimal work cost rate for qu…
Strong and Weak Optimizations in Classical and Quantum Models of Stochastic Processes
Samuel Loomis, James P. Crutchfield
Among the predictive hidden Markov models that describe a given stochastic process, the ε-machine is strongly minimal in that it minimizes every Rényi-based memory measure. Quantum…