Lifeboat Foundation

Note that this does not involve Planck mass fermionic black holes!

A population of massive black holes whose origin is one of the biggest mysteries in modern astronomy has been detected by the LIGO and Virgo gravitational wave detectors.

According to one hypothesis, these objects may have formed in the very early Universe and may compose dark matter, a mysterious substance filling the Universe. A team of scientists has announced the results of nearly 20-year-long observations indicating that such massive black holes may comprise at most a few percent of dark matter. Therefore, another explanation is needed for gravitational wave sources.

Continue reading “Black Holes and Dark Revelations: Gravitational Waves Provide New Clues to the Composition of Dark Matter” »

This essay addresses Cartesian duality and how its implicit dialectic might be repaired using physics and information theory. Our agenda is to describe a key distinction in the physical sciences that may provide a foundation for the distinction between mind and matter, and between sentient and intentional systems. From this perspective, it becomes tenable to talk about the physics of sentience and ‘forces’ that underwrite our beliefs (in the sense of probability distributions represented by our internal states), which may ground our mental states and consciousness. We will refer to this view as Markovian monism, which entails two claims: fundamentally, there is only one type of thing and only one type of irreducible property (hence monism). All systems possessing a Markov blanket have properties that are relevant for understanding the mind and consciousness: if such systems have mental properties, then they have them partly by virtue of possessing a Markov blanket (hence Markovian). Markovian monism rests upon the information geometry of random dynamic systems. In brief, the information geometry induced in any system—whose internal states can be distinguished from external states—must acquire a dual aspect. This dual aspect concerns the (intrinsic) information geometry of the probabilistic evolution of internal states and a separate (extrinsic) information geometry of probabilistic beliefs about external states that are parameterised by internal states. We call these intrinsic (i.e., mechanical, or state-based) and extrinsic (i.e., Markovian, or belief-based) information geometries, respectively. Although these mathematical notions may sound complicated, they are fairly straightforward to handle, and may offer a means through which to frame the origins of consciousness.

Keywords: consciousness, information geometry, Markovian monism.

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Philosophical and theoretical debates on the multiple realisability of the cognitive have historically influenced discussions of the possible systems capable of instantiating complex functions like memory, learning, goal-directedness, and decision-making. These debates have had the corollary of undermining, if not altogether neglecting, the materiality and corporeality of cognition-treating material, living processes as “hardware” problems that can be abstracted out and, in principle, implemented in a variety of materials-in particular on digital computers and in the form of state-of-the-art neural networks. In sum, the matter in se has been taken not to matter for cognition. However, in this paper, we argue that the materiality of cognition-and the living, self-organizing processes that it enables-requires a more detailed assessment when understanding the nature of cognition and recreating it in the field of embodied robotics. Or, in slogan form, that the matter matters for cognitive form and function. We pull from the fields of Active Matter Physics, Soft Robotics, and Basal Cognition literature to suggest that the imbrication between material and cognitive processes is closer than standard accounts of multiple realisability suggest. In light of this, we propose upgrading the notion of multiple realisability from the standard version-what we call 1.0-to a more nuanced conception 2.0 to better reflect the recent empirical advancements, while at the same time averting many of the problems that have been raised for it. These fields are actively reshaping the terrain in which we understand materiality and how it enables, mediates, and constrains cognition. We propose that taking the materiality of our embodied, precarious nature seriously furnishes an important research avenue for the development of embodied robots that autonomously value, engage, and interact with the environment in a goal-directed manner, in response to existential needs of survival, persistence, and, ultimately, reproduction. Thus, we argue that by placing further emphasis on the soft, active, and plastic nature of the materials that constitute cognitive embodiment, we can move further in the direction of autonomous embodied robots and Artificial Intelligence.

Keywords: active matter physics; artificial intelligence; basal cognition; embodied cognition; fine-grained functionalism; functionalism; multiple realisability; soft robotics.

Copyright © 2022 Harrison, Rorot and Laukaityte.

New studies suggest the Nancy Grace Roman Space Telescope could detect primordial black holes from the early universe, potentially confirming their role in cosmic inflation and as components of dark matter.

When astrophysicists observe the cosmos, they see different types of black holes. They range from gargantuan supermassive black holes with billions of solar masses to difficult-to-find intermediate-mass black holes (IMBHs) all the way down to smaller stellar-mass black holes.

Continue reading “From the Dawn of Time: Hunting for Primordial Black Holes With NASA’s Roman Space Telescope” »

Domain walls, long a divisive topic in physics, may be ideal explanations for some bizarre cosmic quirks.

By Anil Ananthaswamy

“As long as they live for long enough, they will always become large cosmological beasts,” says Ricardo Ferreira, a cosmologist at the University of Coimbra in Portugal. He’s not talking about actual beasts but rather about hypothetical humongous sheets of spacetime that could divide one region of the universe from another. Such so-called domain walls are the natural outcome of theories that try to solve some of the deepest mysteries in physics, such as the origins of gravity. As Ferreira says, however, had they formed after the big bang, by today they’d be the dominant source of energy in our universe, and there’s no evidence that’s the case. So any theory invoking their existence has been considered suspect—until now, perhaps.

From the dynamical point of view, most cognitive phenomena are hierarchical, transient and sequential. Such cognitive spatio-temporal processes can be represented by a set of sequential metastable dynamical states together with their associatedions: The state is quasi-stationary close to one metastable state before a rapidion to another state. Hence, we postulate that metastable states are the central players in cognitive information processing. Based on the analogy of quasiparticles as elementary units in physics, we introduce here the quantum of cognitive information dynamics, which we term “cognon”. A cognon, or dynamical unit of thought, is represented by a robust finite chain of metastable neural states. Cognons can be organized at multiple hierarchical levels and coordinate complex cognitive information representations.

This month in 1,871, James Clerk demonstrated entropy with a thought experiment now known as’s Demon.

The American Physical Society is a nonprofit membership organization working to advance physics by fostering a vibrant, inclusive, and global community dedicated to science and society.

Growth of data eases the way to access the world but requires increasing amounts of energy to store and process. Neuromorphic electronics has emerged in the last decade, inspired by biological neurons and synapses, with in-memory computing ability, extenuating the ‘von Neumann bottleneck’ between the memory and processor and offering a promising solution to reduce the efforts both in data storage and processing, thanks to their multi-bit non-volatility, biology-emulated characteristics, and silicon compatibility. This work reviews the recent advances in emerging memristive devices for artificial neuron and synapse applications, including memory and data-processing ability: the physics and characteristics are discussed first, i.e., valence changing, electrochemical metallization, phase changing, interfaced-controlling, charge-trapping, ferroelectric tunnelling, and spin-transfer torquing. Next, we propose a universal benchmark for the artificial synapse and neuron devices on spiking energy consumption, standby power consumption, and spike timing. Based on the benchmark, we address the challenges, suggest the guidelines for intra-device and inter-device design, and provide an outlook for the neuromorphic applications of resistive switching-based artificial neuron and synapse devices.

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Physics meets machine learning.

The Progress and Promise for Science in Indonesia Regional Special Feature focuses on biodiversity and climate change, highlighting research based on the unique geology and biology of a nation comprising more than 17,600 islands, containing about 10 percent of the world’s remaining tropical forests, and home to over 300,000 species of wildlife.