Foresight Biotech & Health Extension Meeting sponsored by 100 Plus Capital.
Program & apply to join: https://foresight.org/biotech-health-extension-program/
Jennifer Garrison, Buck Institute.
Reframing Health and Aging through the Lens of Reproduct.
Digitalization generated 4 percent of the total greenhouse emissions in 2020.
More than half of the digital data firms generate is collected, processed, and stored for single-use purposes. Often, it is never re-used. This could be your multiple near-identical images held on Google Photos or iCloud, a business’s outdated spreadsheets that will never be used again, or data from internet of things sensors that have no purpose.
This “dark data” is anchored to the real world by the energy it requires. Even data that is stored and never used again takes up space on servers — typically huge banks of computers in warehouses. Those computers and those warehouses all use lots of electricity.
Continue reading “What is ‘dark data’? How digital information is quietly sapping energy” »
Circa 2019
Lodestone, a naturally-occurring iron oxide, was the first persistently magnetic material known to humans. The Han Chinese used it for divining boards 2,200 years ago; ancient Greeks puzzled over why iron was attracted to it; and, Arab merchants placed it in bowls of water to watch the magnet point the way to Mecca. In modern times, scientists have used magnets to read and record data on hard drives and form detailed images of bones, cells and even atoms.
Throughout this history, one thing has remained constant: Our magnets have been made from solid materials. But what if scientists could make magnetic devices out of liquids?
Continue reading “This New Liquid Is Magnetic, and Mesmerizing” »
A method to draw data in an area smaller than 10 nanometers has been proposed in a recent study published in Physical Review Letters
A joint research team led by Professor Daesu Lee (Department of Physics) of POSTECH, Professor Se Young Park (Department of Physics) at Soongsil University, and Dr. Ji Hye Lee (Department of Physics and Astronomy) of Seoul National University has proposed a method for densely storing data by “poking” with a sharp probe. This method utilizes a material in the metastable state, whose properties change easily even with slight stimulation.
A thin film of metastable ferroelectric calcium titanate (CaTiO3) enables the polarization switching of a material even with a slight pressure of a probe: A very weak force of 100 nanonewtons (nN) is more than enough. The joint research team succeeded in making the width of the polarization path smaller than 10 nm by using this force and found the way to dramatically increase the capacity of data storage. This is because the smaller the size of the path, the more data the single material can store.
Two milliseconds—or two thousandths of a second—is an extraordinarily long time in the world of quantum computing. On these timescales the blink of an eye—at one 10th of a second—is like an eternity.
Now a team of researchers at UNSW Sydney has broken new ground in proving that ‘spin qubits’—properties of electrons representing the basic units of information in quantum computers—can hold information for up to two milliseconds. Known as ‘coherence time’, the duration of time that qubits can be manipulated in increasingly complicated calculations, the achievement is 100 times longer than previous benchmarks in the same quantum processor.
Microprocessors in smartphones, computers, and data centers process information by manipulating electrons through solid semiconductors, but our brains have a different system. They rely on the manipulation of ions in liquid to process information.
Inspired by the brain, researchers have long been seeking to develop “ionics” in an aqueous solution. While ions in water move slower than electrons in semiconductors, scientists think the diversity of ionic species with different physical and chemical properties could be harnessed for richer and more diverse information processing.
Ionic computing, however, is still in its early days. To date, labs have only developed individual ionic devices such as ionic diodes and transistors, but no one has put many such devices together into a more complex circuit for computing until now.
The concept of “symmetry” is essential to fundamental physics: a crucial element in everything from subatomic particles to macroscopic crystals. Accordingly, a lack of symmetry—or asymmetry—can drastically affect the properties of a given system.
Qubits, the quantum analog of computer bits for quantum computers, are extremely sensitive—the barest disturbance in a qubit system is enough for it to lose any quantum information it might have carried. Given this fragility, it seems intuitive that qubits would be most stable in a symmetric environment. However, for a certain type of qubit—a molecular qubit—the opposite is true.
Researchers from the University of Chicago’s Pritzker School of Molecular Engineering (PME), the University of Glasgow, and the Massachusetts Institute of Technology have found that molecular qubits are much more stable in an asymmetric environment, expanding the possible applications of such qubits, especially as biological quantum sensors.
Researchers at QuTech—a collaboration between the Delft University of Technology and TNO—have engineered a record number of six, silicon-based, spin qubits in a fully interoperable array. Importantly, the qubits can be operated with a low error-rate that is achieved with a new chip design, an automated calibration procedure, and new methods for qubit initialization and readout. These advances will contribute to a scalable quantum computer based on silicon. The results are published in Nature today.
Different materials can be used to produce qubits, the quantum analog to the bit of the classical computer, but no one knows which material will turn out to be best to build a large-scale quantum computer. To date there have only been smaller demonstrations of silicon quantum chips with high quality qubit operations. Now, researchers from QuTech, led by Prof. Lieven Vandersypen, have produced a six qubit chip in silicon that operates with low error-rates. This is a major step towards a fault-tolerant quantum computer using silicon.
To make the qubits, individual electrons are placed in a linear array of six “quantum dots” spaced 90 nanometers apart. The array of quantum dots is made in a silicon chip with structures that closely resemble the transistor—a common component in every computer chip. A quantum mechanical property called spin is used to define a qubit with its orientation defining the 0 or 1 logical state. The team used finely-tuned microwave radiation, magnetic fields, and electric potentials to control and measure the spin of individual electrons and make them interact with each other.
Physicists at UC Santa Barbara, the University of Maryland, and the University of Washington have found an answer to the longstanding physics question: How do interparticle interactions affect dynamical localization?
“It’s a really old question inherited from condensed matter physics,” said David Weld, an experimental physicist at UCSB with specialties in ultracold atomic physics and quantum simulation. The question falls into the category of “many-body” physics, which interrogates the physical properties of a quantum system with multiple interacting parts. While many-body problems have been a matter of research and debate for decades, the complexity of these systems, with quantum behaviors such as superposition and entanglement, lead to multitudes of possibilities, making it impossible to solve through calculation alone. “Many aspects of the problem are beyond the reach of modern computers,” Weld added.
Fortunately, this problem was not beyond the reach of an experiment that involves ultracold lithium atoms and lasers. So, what emerges when you introduce interaction in a disordered, chaotic quantum system? A “weird quantum state,” according to Weld. “It’s a state which is anomalous, with properties which in some sense lie between the classical prediction and the non-interacting quantum prediction.”
