Lifeboat Foundation

Scientists from the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory have shown that a type of qubit whose architecture is more amenable to mass production can perform comparably to qubits currently dominating the field. With a series of mathematical analyses, the scientists have provided a roadmap for simpler qubit fabrication that enables robust and reliable manufacturing of these quantum computer building blocks.

Reconfigurable photonic bricks offer flexible and energy-efficient solutions, advancing light-based technology for communication and computing.

After thousands of years as a highly valuable commodity, silk continues to surprise. Now it may help usher in a whole new direction for microelectronics and computing.

A discovery six years ago took the condensed-matter physics world by storm: Ultra-thin carbon stacked in two slightly askew layers became a superconductor, and changing the twist angle between layers could toggle their electrical properties. The landmark 2018 paper describing “magic-angle graphene superlattices” launched a new field called “twistronics,” and the first author was then-MIT graduate student and recent Harvard Junior Fellow Yuan Cao.

Together with Harvard physicists Amir Yacoby, Eric Mazur, and others, Cao and colleagues have built on that foundational work, smoothing a path for more twistronics science by inventing an easier way to twist and study many types of materials.

A new paper in Nature describes the team’s fingernail-sized machine that can twist thin materials at will, replacing the need to fabricate twisted devices one by one. Thin, 2D materials with properties that can be studied and manipulated easily have immense implications for higher-performance transistors, optical devices such as solar cells, and quantum computers, among other things.

A quantum computing protocol makes it possible to extract energy from seemingly empty space, teleport it to a new location, then store it for later use.

By Karmela Padavic-Callaghan

In a recent paper published in PRX Quantum, a team of researchers from Osaka University and RIKEN presented an approach to improve the fault-tolerance of color codes, a type of quantum error correction (QEC) code. Their method, known as Flagged Weight Optimization (FWO), targets the underlying challenges of color-code architectures, which historically suffer from lower thresholds under circuit-level noise. By optimizing the decoder weights based on the outcomes of flag qubits, this method improves the threshold values of color codes.

Color codes are an alternative to surface codes in quantum error correction that implement all Clifford gates transversally, making them a potential solution for low-overhead quantum computing, as noted by the paper. However, their practical use has been limited thus far by the relatively low fault-tolerance thresholds under circuit-level noise. Traditional methods of stabilizer measurement, which involve high-weight stabilizers acting on numerous qubits, introduce substantial circuit depth and errors, ultimately leading to lower overall performance.

The research team focused on two color-code lattices—the (4.8.8) and (6.6.6) color codes. The team noted that while these codes are considered topologically advantageous for QEC, their previous thresholds were relatively low, making them less effective for real-world applications. For example, the threshold for the (4.8.8) color code was previously around 0.14%, limiting its use in fault-tolerant computing.

Researchers say they’ve built and tested a ‘structural battery’ that packs a device or EV’s chassis with energy, saving a ton of weight. It could unlock smartphones as thin as credit cards, laptops at half the weight and a 70% boost to EV range.

EVs rely heavily – pun intended – on large lithium-ion batteries to cover long distances. Researchers at Chalmers University of Technology wondered if they could build a battery that doubles as the load-bearing material holding the car together, and shed some weight.

As part of their work on what they call ‘massless energy storage,’ the research team in Sweden has developed a battery made of a carbon fiber composite. It promises similar stiffness to aluminum, while also being capable of storing a fair bit of energy – enough to be used commercially.

For billions of years, life has used long molecules of deoxyribonucleic acid, or DNA, to store information and solve problems.

Today engineers are putting their own spin on DNA computing, to both record data and serve as biological computers, yet until now they’ve struggled to design a synthetic system that can store and perform tasks at the same time.

New research has now demonstrated it’s possible to package and present DNA so it can manage both, providing a full suite of computing functions out of strings of nucleic acids. Specifically, we’re talking about storing, reading, erasing, moving, and rewriting data, and handling these functions in programmable and repeatable ways, similar to how a conventional computer would operate.

However, more recent research suggests there are likely countless other possibilities for how life might emerge through potential chemical combinations. As the British chemist Lee Cronin, the American theoretical physicist Sara Walker and others have recently argued, seeking near-miraculous coincidences of chemistry can narrow our ability to find other processes meaningful to life. In fact, most chemical reactions, whether they take place on Earth or elsewhere in the Universe, are not connected to life. Chemistry alone is not enough to identify whether something is alive, which is why researchers seeking the origin of life must use other methods to make accurate judgments.

Today, ‘adaptive function’ is the primary criterion for identifying the right kinds of biotic chemistry that give rise to life, as the theoretical biologist Michael Lachmann (our colleague at the Santa Fe Institute) likes to point out. In the sciences, adaptive function refers to an organism’s capacity to biologically change, evolve or, put another way, solve problems. ‘Problem-solving’ may seem more closely related to the domains of society, culture and technology than to the domain of biology. We might think of the problem of migrating to new islands, which was solved when humans learned to navigate ocean currents, or the problem of plotting trajectories, which our species solved by learning to calculate angles, or even the problem of shelter, which we solved by building homes. But genetic evolution also involves problem-solving. Insect wings solve the ‘problem’ of flight. Optical lenses that focus light solve the ‘problem’ of vision. And the kidneys solve the ‘problem’ of filtering blood. This kind of biological problem-solving – an outcome of natural selection and genetic drift – is conventionally called ‘adaptation’. Though it is crucial to the evolution of life, new research suggests it may also be crucial to the origins of life.

This problem-solving perspective is radically altering our knowledge of the Universe. Life is starting to look a lot less like an outcome of chemistry and physics, and more like a computational process.