Lifeboat Foundation

A summary of an argumentative paper by Litt, Eliasmith, Kroon, Weinstein and Thagard.

Last month, a team from North Carolina State University and Johns Hopkins University found a workaround. They embedded DNA molecules, encoding multiple images, into a branched gel-like structure resembling a brain cell.

Dubbed “dendricolloids,” the structures stored DNA files far better than those freeze-dried alone. DNA within dendricolloids can be repeatedly dried and rehydrated over roughly 170 times without damaging stored data. According to one estimate, each DNA strand could last over two million years at normal freezer temperatures.

Unlike previous DNA computers, the data can be erased and replaced like memory on classical computers to solve multiple problems—including a simple chess game and sudoku.

Researchers from Japan and the Michigan Technological University have succeeded in building a molecular computer that, more than any previous project of its kind, can replicate the inner mechanisms of the human brain, repairing itself and mimicking the massive parallelism that allows our brains to process information like no silicon-based computer can.

A relatively new technology, molecular electronics is an interdisciplinary pursuit that may very well prove the long-term solution to validate Moore’s law well into the next century. A molecular computer is made of organic molecules instead of silicon. Chips built this way are not only potentially much smaller but also, because of the way they can be networked, able to do things that no other traditional computer, regardless of its speed, can do.

“Modern computers are quite fast, capable of executing trillions of instructions a second, but they can’t match the intelligent performance of our brain,” Michigan Tech physicist Ranjit Pati commented. “Our neurons only fire about a thousand times per second. But I can see you, recognize you, talk with you, and hear someone walking by in the hallway almost instantaneously, a Herculean task for even the fastest computer.”

Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes. Here the authors create layered assemblies of genetically encoded devices that perform non-binary logic computation and signal processing using combinatorial promoters and feedback regulation.

Molecular materials for computing progress intensively but the performance and reliability still lag behind. Here the authors assess the current state of computing with molecular-based materials and describe two issues as the basis of a new computing technology: continued exploration of molecular electronic properties and process development for on-chip integration.

Even those of us who aren’t physicists have an intuitive understanding of classical physics — we can predict what will happen when we throw a ball, use a salad spinner, or ease up on the gas pedal.

But atomic and subatomic particles don’t follow these ordinary rules of reality. “It turns out that at really small scales there are a different set of rules called quantum physics,” said Travis Nicholson. “These rules are bizarre and interesting.” (Think Schrodinger’s cat and Einstein’s “spooky action at a distance.”)

Nicholson is an assistant professor with joint appointments in Physics and Electrical and Computer Engineering. The physicist in him likes doing experiments to advance our knowledge of quantum mechanics; the engineer in him likes figuring out how to harness that knowledge to build quantum computers that will be vastly more powerful than today’s computers.

The topological quantum computer still exists only in theory but, if possible, would be the most stable and powerful computing machine in the world. However, it requires a special type of qubit (quantum bit) that has yet to be realized and manipulated.

Quantum entanglement is a fascinating feature of quantum physics—the theory of the very small. If two particles are quantum-entangled, the state of one particle is tied to that of the other, no matter how far apart the particles are. This mind-bending phenomenon, which has no analog in classical physics, has been observed in a wide variety of systems and has found several important applications, such as quantum cryptography and quantum computing.

Certain materials involving copper and oxygen display superconductivity (where electricity flows without resistance) at relatively high — but still frigid — temperatures below minus 140 degrees Celsius. At higher temperatures, these materials fall into what’s called the pseudogap state, where they sometimes act like a normal metal and sometimes act more like semiconductors. Scientists have found that the pseudogap shows up in all so-called high-temperature superconducting materials. But they didn’t understand why or how it shows up, or if it sticks around as the temperature drops to absolute zero (minus 273.15 degrees Celsius), the unreachable lower limit of temperature at which molecular motion stops.

By better understanding how the pseudogap appears and how it relates to the theoretical properties of the superconductive materials at absolute zero, scientists are getting a clearer picture of those materials, says study co-author Antoine Georges, director of the Flatiron Institute’s Center for Computational Quantum Physics.

“It’s like you have a landscape and a lot of fog, and previously you could just see a few valleys and a few peaks,” he says. “Now the fog is dissipating, and we can see more of the full landscape. It’s really quite an exciting time.”