Unconventional computing devices are increasingly of interest as they can
operate in environments hostile to silicon-based electronics, or compute in
ways that traditional electronics cannot. Mechanical computers, wherein
information processing is a material property emerging from the interaction of
components with the environment, are one such class of devices. This
information processing can be manifested in various physical substrates, one of
which is granular matter. In a granular assembly, vibration can be treated as
the information-bearing mode. This can be exploited to realize "polycomputing":
materials can be evolved such that a single grain within them can report the
result of multiple logical operations simultaneously at different frequencies,
without recourse to quantum effects. Here, we demonstrate the evolution of a
material in which one grain acts simultaneously as two different NAND gates at
two different frequencies. NAND gates are of interest as any logical operations
can be built from them. Moreover, they are nonlinear thus demonstrating a step
toward general-purpose, computationally dense mechanical computers.
Polycomputation was found to be distributed across each evolved material,
suggesting the material's robustness. With recent advances in material
sciences, hardware realization of these materials may eventually provide
devices that challenge the computational density of traditional computers.

本文旨在通过研究基于颗粒堆积的力学计算机，探讨在不依赖于量子效应的情况下实现多逻辑计算的 “聚合计算” 模式，并演示了一种由颗粒进化而成的物质，用于同时实现两个不同频率下的两个 NAND 门。这种聚合计算方法可以在不同的物理基质上实现，为未来材料科学领域提供了有趣的前景。

颗粒物质中的通用机械多计算

Universal Mechanical Polycomputation in Granular Matter

The applicability of computational models to the biological world is an
active topic of debate. We argue that a useful path forward results from
abandoning hard boundaries between categories and adopting an
observer-dependent, pragmatic view. Such a view dissolves the contingent
dichotomies driven by human cognitive biases (e.g., tendency to oversimplify)
and prior technological limitations in favor of a more continuous, gradualist
view necessitated by the study of evolution, developmental biology, and
intelligent machines. Efforts to re-shape living systems for biomedical or
bioengineering purposes require prediction and control of their function at
multiple scales. This is challenging for many reasons, one of which is that
living systems perform multiple functions in the same place at the same time.
We refer to this as "polycomputing" - the ability of the same substrate to
simultaneously compute different things. This ability is an important way in
which living things are a kind of computer, but not the familiar, linear,
deterministic kind; rather, living things are computers in the broad sense of
computational materials as reported in the rapidly-growing physical computing
literature. We argue that an observer-centered framework for the computations
performed by evolved and designed systems will improve the understanding of
meso-scale events, as it has already done at quantum and relativistic scales.
Here, we review examples of biological and technological polycomputing, and
develop the idea that overloading of different functions on the same hardware
is an important design principle that helps understand and build both evolved
and designed systems. Learning to hack existing polycomputing substrates, as
well as evolve and design new ones, will have massive impacts on regenerative
medicine, robotics, and computer engineering.

我们认为将硬分类界限视为暂时的、观察者相关的、实用主义的观点是有用的，这种观点有助于我们理解生物与技术中的多计算、多功能原则，并有助于我们理解和设计演化和设计系统的方式。