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Category: computing – Page 2

What is Time? Stephen Wolfram’s Groundbreaking New Theory

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What is time? Is it just a ticking clock, or is it something more profound?

In this thought-provoking episode of Into the Impossible, Stephen Wolfram challenges everything we know about time, offering a revolutionary computational perspective that could forever change how we understand the universe.

Stephen Wolfram is a computer scientist, physicist, and businessman. He is the founder and CEO of Wolfram Research and the creator of Mathematica, Wolfram Alpha, and Wolfram Language. Over the course of 4 decades, he has pioneered the development & application of computational thinking. He has been responsible for many discoveries, inventions & innovations in science, technology, and business.

He argues that time is the inevitable progress of computation in the universe, where simple rules can lead to complex behaviors. This concept, termed computational irreducibility, implies that time has a rigid structure and that our perception of it is limited by our computational capabilities. Wolfram also explores the relationship between time, space, and gravity, suggesting that dark matter might be a feature of the structure of space.

Tune in to discover the true nature of time.

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Breakthrough Simulation Maps Every Star in The Milky Way in Scientific First

The Milky Way contains more than 100 billion stars, each following its own evolutionary path through birth, life, and sometimes violent death.

For decades, astrophysicists have dreamed of creating a complete simulation of our galaxy, a digital twin that could test theories about how galaxies form and evolve. That dream has always crashed against an impossible computational wall.

Until now.

Quantum photonic chip integrates light-emitting molecules with single-mode waveguides

Photonic quantum processors, devices that can process information leveraging quantum mechanical effects and particles of light (photons), have shown promise for numerous applications, ranging from computations and communications to the simulation of complex quantum systems.

To be deployed in real-world settings, however, these photonic chips should reliably integrate many deterministic and indistinguishable single-photon sources on a single chip.

So far, achieving this has proved highly challenging. Most such photonic quantum chips developed so far utilize solid-state single-photon emitters that are limited by so-called spectral diffusion (i.e., the random “wandering” of their emission frequency).

Quantum ground states: Scalable counterdiabatic driving technique enables reliable and rapid preparation

Quantum ground states are the states at which quantum systems have the minimum possible energy. Quantum computers are increasingly being used to analyze the ground states of interesting systems, which could in turn inform the design of new materials, chemical compounds, pharmaceutical drugs and other valuable goods.

The reliable preparation of quantum ground states has been a long-standing goal within the physics research community. One quantum computing method to prepare ground states and other desired states is known as adiabatic state preparation.

This is a process that starts from an initial Hamiltonian, a mathematical operator that encodes a system’s total energy and for which the ground state is known, gradually changing it to reach a final Hamiltonian, which encodes the final ground state.

Single-photon switch could enable photonic computing

There are few technologies more fundamental to modern life than the ability to control light with precision. From fiber-optic communications to quantum sensors, the manipulation of photons underpins much of our digital infrastructure. Yet one capability has remained frustratingly out of reach: controlling light with light itself at the most fundamental level using single photons to switch or modulate powerful optical beams.

Now, researchers at Purdue University have achieved this long-sought milestone, demonstrating what they call a “photonic transistor” that operates at single-photon intensities.

Their findings, published in the journal Nature Nanotechnology, report a nonlinear refractive index several orders of magnitude higher than the best-known materials, a leap that could finally make photonic computing practical.

Symmetry simplifies quantum noise analysis, paving way for better error correction

Researchers from the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, and Johns Hopkins University in Baltimore have achieved a breakthrough in quantum noise characterization in quantum systems—a key step toward reliably managing errors in quantum computing.

Their findings, published in Physical Review Letters, make important strides in addressing a long-standing obstacle to developing useful quantum computers.

Noise in quantum systems can come from traditional sources, like temperature swings, vibration, and electrical interference, as well as from atomic-level activity, like spin and magnetic fields, associated with quantum processing.

Stunning Results: Revolutionary Retinal Chip Lets Patients With Severe Vision Loss Read Again

A wireless implant helped patients with severe macular degeneration regain usable vision. The results point toward a new future for vision restoration. A wireless retinal implant has been shown to restore central vision in people with advanced age-related macular degeneration (AMD), according to

If Quantum Computing Is Solving “Impossible” Questions, How Do We Know They’re Right?

A new Swinburne study is addressing a core paradox: if quantum computing is solving problems that cannot be checked by conventional methods, how can we be certain the results are correct? Quantum computing has the potential to tackle problems once thought unsolvable in areas including physics, me

A New Bridge Links the Strange Math of Infinity to Computer Science

All of modern mathematics is built on the foundation of set theory, the study of how to organize abstract collections of objects. But in general, research mathematicians don’t need to think about it when they’re solving their problems. They can take it for granted that sets behave the way they’d expect, and carry on with their work.

Descriptive set theorists are an exception. This small community of mathematicians never stopped studying the fundamental nature of sets — particularly the strange infinite ones that other mathematicians ignore.

Their field just got a lot less lonely. In 2023, a mathematician named Anton Bernshteyn (opens a new tab) published a deep and surprising connection (opens a new tab) between the remote mathematical frontier of descriptive set theory and modern computer science.

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