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.
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 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.
This is a ~1 hour 12 minute talk titled “Computational Symbiogenesis” by Blaise Agüera y Arcas (https://research.google/people/106776/?&type=google), given for our symposium on the Platonic Space (https://thoughtforms.life/symposium-on-the-platonic-space/).
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.
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.
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.
