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SOME PHYSICISTS SUGGEST GRAVITY ISN’T A FORCE AT ALL — BUT A QUANTUM ECHO OF ENTANGLEMENT

Gravity is the most familiar force in human experience, yet it remains the least understood at a fundamental level. Despite centuries of study—from Newton’s law of universal gravitation to Einstein’s general theory of relativity—gravity stubbornly resists unification with quantum mechanics. In recent decades, this tension has led some physicists to propose a radical rethinking of gravity’s nature. According to these ideas, gravity may not be a fundamental force at all, but instead an emergent effect arising from quantum entanglement and the flow of information in spacetime.

This perspective represents a profound conceptual shift. Rather than treating gravity as something particles “exert” on one another, these theories suggest it emerges statistically, much like temperature arises from the collective motion of atoms. This article examines the scientific foundations of this idea, the key theoretical frameworks supporting it, and the evidence—both suggestive and incomplete—that motivates such claims. By analyzing gravity through quantum, thermodynamic, and informational lenses, we gain insight into one of the most ambitious research directions in modern theoretical physics.

The Standard Model of particle physics successfully describes three of the four fundamental interactions: electromagnetism, the weak force, and the strong force. Gravity, however, remains outside this framework. Attempts to quantize gravity using the same methods applied to other forces lead to mathematical infinities that cannot be renormalized.

Exploration of exoplanets: A mathematical solution for investigating their atmospheres

Dr. Leonardos Gkouvelis, researcher at LMU’s University Observatory Munich and member of the ORIGINS Excellence Cluster, has solved a fundamental mathematical problem that had obstructed the interpretation of exoplanet atmospheres for decades. In a paper published in The Astrophysical Journal, Gkouvelis presents the first closed-form analytical theory of transmission spectroscopy that accounts for how atmospheric opacity varies with pressure—an effect that is crucial in the scientific exploration of real atmospheres but had until now been considered mathematically intractable.

For more than 30 years, analytical models were based on a “simplified” atmosphere, as the full mathematical treatment requires solving a complex geometric integral in the presence of altitude-dependent opacity—a problem that could only be tackled using expensive numerical simulations. However, this limitation concealed how the true vertical structure of an atmosphere alters the signals observed by telescopes.

The new model provides key insights into why many exoplanet atmospheres display “muted” spectral features, directly links laboratory molecular-physics data with astronomical observations, and significantly improves agreement with real data—both for Earth’s atmosphere and for high-precision observations of exoplanets.

Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more energy-efficient computation. In this computing method, input data are encoded as a set of temperatures using the waste heat already present in a device.

The flow and distribution of heat through a specially designed material forms the basis of the calculation. Then the output is represented by the power collected at the other end, which is a thermostat at a fixed temperature.

The researchers used these structures to perform matrix vector multiplication with more than 99% accuracy. Matrix multiplication is the fundamental mathematical technique machine-learning models like LLMs utilize to process information and make predictions.

Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, or in other words, what type of cells they will become, is influenced both by predictable biological signals and random physiological fluctuations.

Over the past decades, medical researchers and neuroscientists have been able to study these processes in greater depth, using a technique known as single-cell RNA sequencing (scRNA-seq). This is an experimental tool that can be used to measure the gene activity of individual cells.

To better understand how cells develop over time, researchers also rely on mathematical models. One of these models, dubbed the drift-diffusion equation, describes the evolution of systems as the combination of predictable changes (i.e., drift) and randomness (i.e., diffusion).

Elon Musk Holds Surprise Talk At The World Economic Forum In Davos

The musk blueprint: navigating the supersonic tsunami to hyperabundance when exponential curves multiply: understanding the triple acceleration.

On January 22, 2026, Elon Musk sat down with BlackRock CEO Larry Fink at the World Economic Forum in Davos and delivered what may be the most important articulation of humanity’s near-term trajectory since the invention of the internet.

Not because Musk said anything fundamentally new—his companies have been demonstrating this reality for years—but because he connected the dots in a way that makes the path to hyperabundance undeniable.

[Watch Elon Musk’s full WEF interview]

This is not visionary speculation.

This is engineering analysis from someone building the physical infrastructure of abundance in real-time.

Scientists Uncover Hidden Weakness in Quantum Encryption

Quantum key distribution (QKD) is a next generation method for protecting digital communications by drawing on the fundamental behavior of quantum particles. Instead of relying on mathematical complexity alone, QKD allows two users to establish a shared secret key in a way that is inherently resistant to interception, even if the communication channel itself is not private.

When an unauthorized observer attempts to extract information, the quantum states carrying the data are unavoidably altered, creating telltale disturbances that signal a potential security breach.

The real-world performance of QKD systems, however, depends on precise control of the physical link between sender and receiver. One of the most influential factors is pointing error, which occurs when the transmitted beam does not perfectly align with the receiving device.

Neuropsychiatric symptoms in cognitive decline and Alzheimer’s disease: biomarker discovery using plasma proteomics

Placental toxicology progress!

Commonly used in vitro and in vivo placental models capture key placental functions and toxicity mechanisms, but have significant limitations.

The physiological relevance of placental models varies, with a general hierarchy of simple in vitro complex in vitro/ organ-on-chip in vivo, but species-of origin considerations may alter their relevance to human physiology.

Cellular, rodent, human, and computational modeling systems provide insights into placental transport, physiology, and toxicology linked to maternal–fetal health.

Recent advances in 3D culture and microfluidic technologies offer more physiologically relevant models for studying the placenta.

Mathematical modeling approaches can integrate mechanistic physiological data and exposure assessments to define key toxicokinetic parameters.

Environmental chemical concentrations and omic data obtained from placental tissues can link toxicant influences on placental function to adverse birth outcomes.

Specialized transporters relay lipids to cellular targets

In addition to providing energy, lipids are also essential building blocks of our cell membranes. However, despite their importance, they remain poorly understood. A research team has revealed for the first time the secrets of their transport within cells. Each lipid uses a limited number of proteins to move from its place of production to its place of action. The team has also compiled an inventory of the proteins involved in the transport of hundreds of lipids.

These findings, published in the journal Nature, provide a better picture of the functioning of our cells, as well as of many genetic and metabolic disorders, such as diabetes and Alzheimer’s disease.

Biologists brought together more than a hundred transfer proteins with hundreds of different lipids. The aim was to obtain the most comprehensive list possible of the ‘pairs’ formed between each protein and the lipids it can carry.

To do this, two experimental methods were combined. The first, carried out in a test tube, provides a highly controlled environment, while the second, which more closely corresponds to the inside of a cell, allows researchers to verify how these bonds are formed under near-real conditions. This is a world first on such a scale and at such a level of complexity. “The ‘‘couples’’ identified show that transfer proteins are not “buses” capable of transporting most lipids, but private chauffeurs with specific characteristics,” explains the senior author.

Scientists have been able to determine, using advanced mathematical models, how three transfer proteins recognise, among all lipids, those that they actually transport. ScienceMission sciencenewshighlights.

Video: Why ‘basic science’ is the foundation of innovation

At first glance, some scientific research can seem, well, impractical. When physicists began exploring the strange, subatomic world of quantum mechanics a century ago, they weren’t trying to build better medical tools or high-speed internet. They were simply curious about how the universe worked at its most fundamental level.

Yet without that “curiosity-driven” research—often called basic science—the modern world would look unrecognizable.

“Basic science drives the really big discoveries,” says Steve Kahn, UC Berkeley’s dean of mathematical and physical sciences. “Those paradigm changes are what really drive innovation.”

Sam Altman Cornered by Discovery: Intent & Emails in Elon’s OpenAI Lawsuit

Elon Musk’s lawsuit against OpenAI and his own ambitious plans for AI and tech innovations, including new devices and massive growth for his companies, are positioning him for a major impact on the tech industry, but also come with significant challenges and risks ## Questions to inspire discussion.

Legal Risk Management.

🔍 Q: How does the discovery process threaten OpenAI regardless of lawsuit outcome?

A: Discovery forces exposure of sensitive internal information including Greg Brockman’s 2017 diary entries revealing intent to become for-profit and violating prior agreements with Elon Musk, creating reputational damage and investor uncertainty even if OpenAI wins the case.

⏱️ Q: Why is lawsuit timing particularly damaging to OpenAI’s competitive position?

A: The lawsuit hits during OpenAI’s massive capital raise preparation, forcing delays in fundraising and implementation that allow competitors like Google and Anthropic to advance while OpenAI falls behind, similar to how Meta became less relevant in the AI race.

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