The encryption codes that safeguard internet data today won’t be secure forever.
Future quantum computers may have the processing power and algorithms to crack them.
Nathan Hamlin, instructor and director of the WSU Math Learning Center, is helping to prepare for this eventuality.
If you aren’t already, you’re likely soon to find yourself looking forward to the day when quantum computers will replace regular computers for every day use. The computing power of quantum computers is immense compared to what regular desktops or laptops can do. The downside is, current quantum computing technology are limited by the bulky frameworks and extreme conditions they require in order to function.
Quantum computers need specialized setups in order to sustain and keep quantum bits — the heart of quantum computing — working. These “qubits” are particles in a quantum state of superposition, which allows them to encode and transmit information as 0s and 1s simultaneously. Most computers run on binary bit systems which use either 0s or 1s. Since quantum computers can use both at the same time, they can process more information faster. That being said, Sustaining the life of qubits is particularly difficult, but researchers are investigating quantum computing studies are trying to find ways to prolong the life of qubits using various techniques.
How do molecules rotate in a solvent? Answering this question is complicated, since molecular rotation is perturbed by a very large number of surrounding atoms. For a long time, large-scale computer simulations have been the main approach to model molecule-solvent interactions. However, they are extremely time consuming and sometimes infeasible. Now, Mikhail Lemeshko from the Institute of Science and Technology Austria (IST Austria) has proven that angulons—a certain type of quasiparticle he proposed two years ago—do, in fact, form when a molecule is immersed in superfluid helium. This offers a quick and simple description for rotation of molecules in solvents.
In physics, the concept of quasiparticles is used as a technique to simplify the description of many-particle systems. Namely, instead of modeling strong interactions between trillions of individual particles, one identifies building blocks of the system that are only weakly interacting with one another. These building blocks are called quasiparticles and might consist of groups of particles. For example, to describe air bubbles rising up in water from first principles, one would need to solve an enormous set of equations describing the position and momentum of each water molecule. On the other hand, the bubbles themselves can be treated as individual particles—or quasiparticles—which drastically simplifies the description of the system. As another example, consider a running horse engulfed in a cloud of dust. One can think of it as a quasiparticle consisting of the horse itself and the dust cloud moving along with it.
(Left) Illustration of a synapse in the brain connecting two neurons. (Right) Schematic of artificial synapse (ENODe), which functions as a transistor. It consists of two thin, flexible polymer films (black) with source, drain, and gate terminals, connected by an electrolyte of salty water that permits ions to cross. A voltage pulse applied to the “presynaptic” layer (top) alters the level of oxidation in the “postsynaptic layer” (bottom), triggering current flow between source and drain. (credit: Thomas Splettstoesser/CC and Yoeri van de Burgt et al./Nature Materials)
Stanford University and Sandia National Laboratories researchers have developed an organic artificial synapse based on a new memristor (resistive memory device) design that mimics the way synapses in the brain learn. The new artificial synapse could lead to computers that better recreate the way the human brain processes information. It could also one day directly interface with the human brain.
The new artificial synapse is an electrochemical neuromorphic organic device (dubbed “ENODe”) — a mixed ionic/electronic design that is fundamentally different from existing and other proposed resistive memory devices, which are limited by noise, required high write voltage, and other factors*, the researchers note in a paper published online Feb. 20 in Nature Materials.
I remember a year ago when this 1st came out; nice they are highlighting 1 yr later as a reminder.
British scientists David Thouless, Duncan Haldane and Michael Kosterlitz won this year’s Nobel Prize in Physics “for theoretical discoveries of topological phase transitions and topological phases of matter”. The reference to “theoretical discoveries” makes it tempting to think their work will not have practical applications or affect our lives some day. The opposite may well be true.
To understand the potential, it helps to understand the theory. Most people know that an atom has a nucleus in the middle and electrons orbiting around it. These correspond to different energy levels. When atoms group into substances, all the energy levels of each atom combine into bands of electrons. Each of these so-called energy bands has space for a certain number of electrons. And between each band are gaps in which electrons can’t flow.
If you apply an electrical charge (a flow of extra electrons) to a material, its conductivity is determined by whether the highest energy band has room for more electrons. If it does have room, the material will behave as a conductor. If not, you need extra energy to push the current of electrons into a new empty band and as a result the material behaves as an insulator. Understanding conductivity is vital to electronics, since electronic products ultimately rely on components that are electric conductors, semiconductors and insulators.
General Relativity and quantum theory, the two pillars of modern physics, although notoriously difficult to reconcile, may beautifully work together, as a new paper suggests. Moreover, the spacetime curvature and twisting create, manipulate and communicate quantum information encoded in light.
Electronic circuits are found in almost everything from smartphones to spacecraft and are useful in a variety of computational problems from simple addition to determining the trajectories of interplanetary satellites. At Caltech, a group of researchers led by Assistant Professor of Bioengineering Lulu Qian is working to create circuits using not the usual silicon transistors but strands of DNA.
The Qian group has made the technology of DNA circuits accessible to even novice researchers—including undergraduate students—using a software tool they developed called the Seesaw Compiler. Now, they have experimentally demonstrated that the tool can be used to quickly design DNA circuits that can then be built out of cheap “unpurified” DNA strands, following a systematic wet-lab procedure devised by Qian and colleagues.
A paper describing the work appears in the February 23 issue of Nature Communications.
