Kusumoto, T., Mitarai, K., Fujii, K. et al. Experimental quantum kernel trick with nuclear spins in a solid. npj Quantum Inf 7, 94 (2021). https://doi.org/10.1038/s41534-021-00423-0
Category: quantum physics
Designing better quantum circuits with AI
Researchers from the group of theoretical physicist Hans Briegel have collaborated with NVIDIA to develop an AI method that automatically generates efficient quantum circuits, a key bottleneck in making quantum computers practically useful.
The work was published in Machine Learning: Science and Technology, in a paper titled “Synthesis of discrete–continuous quantum circuits with multimodal diffusion models.”
Before a quantum computer can perform any useful task, a quantum algorithm needs to be translated into a sequence of elementary quantum operations, known as quantum gates. Writing these quantum circuits efficiently is one of the hardest open problems in the field.
Dr. Stuart Hameroff: Consciousness is More than Computation!
13 years ago, I walked into Dr. Stuart Hameroff’s operating room with a camera, a microphone, and a single stubborn question:
Is consciousness computation?
Hameroff, an anesthesiologist and professor at the University of Arizona, and co-author with Sir Roger Penrose of the Orch OR theory, said no.
Emphatically. Unfashionably. Against the entire weight of mainstream neuroscience and Silicon Valley orthodoxy.
At the GF2045 conference, where I first met him, Ray Kurzweil went out of his way to declare Orch OR “totally wrong.” Others called it speculative. Untestable. Unscientific.
Today, in the age of large language models, that argument is no longer a niche dispute among philosophers and physicists. It is the decisive question of our century.
Scientists found a way to cool quantum computers using noise
Quantum computers only work when they are kept extremely cold. The problem is that today’s cooling systems also create noise, which can interfere with the fragile quantum information they are supposed to protect. Researchers at Chalmers University of Technology in Sweden have now introduced a new type of minimal quantum “refrigerator” that turns this challenge into an advantage. Instead of fighting noise, the device partially relies on it to operate. The result is highly precise control over heat and energy flow, which could help make large scale quantum technology possible.
Quantum technology is widely expected to reshape major areas of society. Potential applications include drug discovery, artificial intelligence, logistics optimization, and secure communications. Despite this promise, serious technical barriers still stand in the way of real world use. One of the most difficult challenges is maintaining and controlling the delicate quantum states that make these systems work.
Sunlight-powered generation of correlated photon pairs
Pairs of correlated or entangled photons are a foundational resource in quantum optics. They are most commonly produced through spontaneous parametric down-conversion (SPDC), a nonlinear optical process that typically relies on a stable, coherent laser to pump a nonlinear crystal. Because of this requirement, SPDC has long been viewed as impractical without laboratory-grade laser systems.
Recent studies have shown that fully coherent light is not strictly necessary: Partially coherent sources can also drive SPDC, with their coherence properties transferred to the generated photon pairs. This insight raises a natural and intriguing question—can sunlight, the most abundant natural light source, be used to generate correlated photon pairs?
Using sunlight for SPDC presents clear challenges. Sunlight collected from the ground is inherently unstable, with continuous changes in intensity, angle, and position that interfere with the precise illumination and photon detection required for SPDC experiments. At the same time, sunlight offers a compelling advantage: it removes dependence on lasers and external power sources, opening possibilities for photon-pair generation in remote or extreme environments.
New quantum algorithm solves “impossible” materials problem in seconds
A new quantum-inspired algorithm has cracked a problem so massive that conventional supercomputers struggle to even approach it. Researchers used the method to simulate extraordinarily complex quantum materials known as quasicrystals, opening the door to powerful new quantum devices and ultra-efficient electronics. The work could help scientists design advanced topological qubits and materials for future quantum computers.
Quobly Toolbox Explores Quantum Phase Estimation Pipeline With Tensor Networks
An international collaboration between a French quantum startup and a major Taiwanese electronics manufacturer has yielded a new open-source tool for exploring a critical area of quantum computing. Quobly and Taiwan’s Hon Hai Research Institute, the R&D arm of Foxconn, jointly released a numerical toolbox dedicated to the Quantum Phase Estimation (QPE) algorithm, described as a cornerstone of fault-tolerant quantum computing with major applications in quantum chemistry and materials science. While QPE’s theoretical benefits are understood, simulating its practical resource needs has proven difficult; the toolbox aims to bridge this gap by allowing researchers to explore implementations and their implications. The tool focuses on practical, interpretable numerical experiments, enabling full circuit executions for up to 20 qubits and circuits ranging from 1,000 to 100,000 gates on standard laptops.
Quantum Phase Estimation Toolbox for Molecular Systems
While the theoretical underpinnings of QPE are well established, simulating its practical demands has proven a significant hurdle, limiting exploration beyond simplified models. The toolbox addresses this gap by offering a platform for practical, interpretable numerical experiments, allowing scientists to investigate QPE implementations without requiring access to full-scale quantum hardware, which is currently unavailable. Built upon advanced tensor network techniques and the open-source quimb library, the toolbox facilitates the preparation of initial states using DMRG and matrix product states, and allows encoding of molecular Hamiltonians into quantum circuits through methods like trotterization and qubitization. Researchers can directly compare standard QPE with the single-ancilla Robust Phase Estimation (RPE) method, analyzing circuit depth, gate counts, and potential error sources.
String theory is uniquely derived from basic assumptions about the universe, physicists show
If you could take an apple and break it into smaller and smaller parts, you would find molecules, then atoms, followed by subatomic particles like protons and the quarks and gluons that make them up. You might think you hit the bottom, but, according to string theorists, if you keep going to even smaller scales—about a billion billion times smaller than a proton—you will find more: tiny vibrating strings.
Developed in the 1960s, string theory proposes that everything in the universe is made from invisible strings. The theory arose as a possible solution to the problem of “quantum gravity,” the quest to align quantum mechanics, which describes our world at the smallest scales, with the general theory of relativity, which explains how our universe works on the largest scales (and includes gravity). Researchers have tried to reconcile the two theories—asking, for example, how gravity behaves in the quantum realm—but their equations go berserk, or in mathematical terms, go to infinity.
String theory is a mathematical solution that tames the unruly infinities. It purports that all particles, including the graviton—the hypothetical particle believed to convey the force of gravity—are generated by very small vibrating strings. The math behind string theory requires the strings to vibrate in at least 10 dimensions, rather than the four we live in (three for space and one for time), which is one of the reasons some scientists are not convinced that string theory is correct. But perhaps the biggest challenge for the theory is the ultrahigh energies required for testing it: Such an experiment would require a particle collider the size of a galaxy.