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Category: computing – Page 350

Solving computationally complex problems with probabilistic computing

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According to computational complexity theory, mathematical problems have different levels of difficulty in the context of their solvability. While a classical computer can solve some problems ℗ in polynomial time—i.e., the time required for solving P is a polynomial function of the input size—it often fails to solve NP problems that scale exponentially with the problem size and thus cannot be solved in polynomial time. Classical computers based on semiconductor devices are, therefore, inadequate for solving sufficiently large NP problems.

In this regard, quantum computers are considered promising as they can perform a large number of operations in parallel. This, in turn, speeds up the NP problem-solving process. However, many physical implementations are highly sensitive to thermal fluctuations. As a result, quantum computers often demand stringent experimental conditions such extremely low temperatures for their implementation, making their fabrication complicated and expensive.

Fortunately, there is a lesser-known and as-yet underexplored alternative to quantum computing, known as probabilistic computing. Probabilistic computing utilizes what are called “stochastic nanodevices,” whose operations rely on thermal fluctuations, to solve NP problems efficiently. Unlike in the case of quantum computers, thermal fluctuations facilitate problem solving in probabilistic computing. As a result, probabilistic computing is, in fact, easier to implement in real life.

Timber! The World’s First Wooden Transistor

“It was very curiosity-driven,” says Isak Engquist, a professor at Linköping University who led the effort. “We thought: ‘Can we do it? Let’s do it, let’s put it out there to the scientific community and hope that someone else has something where they see these could actually be of use in reality.’”

“I have colleagues who are at the forefront in a field we call electronic plants. 
 We have worked with dead woods for this project, but the next step might be to integrate it also into living plants.” —Isak Engquist, Linköping University.

Even though the wooden transistor still awaits its killer app, the idea to build wood-based electronics is not as crazy as it sounds. A recent review of wood-based materials reads, “Around 300 million years of tree evolution has yielded over 60,000 woody species, each of which is an engineering masterpiece of nature.” Wood has great structural stability while being highly porous and efficiently transporting water and nutrients. The researchers leveraged these properties to create conducting channels inside the wood’s pores and electrochemically modulate their conductivity with the help of a penetrating electrolyte.

Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short-and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This Perspective discusses select examples of these approaches and provides an outlook on the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.

Scientists Create a Longer-Lasting Exciton that May Open New Possibilities in Quantum Information Science

In a new study, scientists have observed long-lived excitons in a topological material, opening intriguing new research directions for optoelectronics and quantum computing.

Excitons are charge-neutral quasiparticles created when light is absorbed by a semiconductor. Consisting of an excited electron coupled to a lower-energy electron vacancy or hole, an exciton is typically short-lived, surviving only until the electron and hole recombine, which limits its usefulness in applications.

“If we want to make progress in quantum computing and create more sustainable electronics, we need longer exciton lifetimes and new ways of transferring information that don’t rely on the charge of electrons,” said Alessandra Lanzara, who led the study. Lanzara is a senior faculty scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) and a UC Berkeley physics professor. “Here we’re leveraging topological material properties to make an exciton that is long lived and very robust to disorder.”

Stanford team shines light on cryptocurrency, designs photonic circuits to save energy

Cryptocurrency mining is only accessible to those with access to highly discounted energy. The newly-developed low-energy chips will make it possible for everyone to participate in mining profitably.

If you were to ask anyone their feelings about cryptocurrency in 2020, chances are they would respond along the lines of “to the moon”(Crypto investors often use the phrase when they believe that certain cryptocurrencies will rise significantly in price). However, a year later, those sentiments seemed to have jaded. A sense of negativity — FUD (fear, uncertainty, and doubt), as crypto-sympathizers would call it — seemed rife.

Stanford University.

A primary reason behind the fading support of the public, besides bad actors flooding the market with ponzi-like schemes and scams, seemed to be massive numbers of energy consumption floated by crypto and blockchain critics. The biggest question was “How is the world supposed to go greener and rely on these energy-hogging, power-hungry technologies?”

Turbulence in Collisionless Cosmic Plasmas

New computer simulations show that wave-particle interactions endow thin plasmas with an effective viscosity that regulates their turbulent motions and heating.

Most of the regular matter in the Universe is plasma, an ebullient state characterized by charged particles interacting collectively with electromagnetic fields. When individual particles collide on scales much shorter than those of bulk plasma motions, the latter are described well by a 3D fluid theory: magnetohydrodynamics. That condition prevails in the interiors of stars and planets and in protoplanetary accretion disks. But many hot, low-density astrophysical plasma flows are only weakly collisional. Accounting for stellar winds, accretion around black holes, and the motions of the plasma that pervades intergalactic space requires a statistical kinetic description of the particle positions and velocities in a 6D space. Numerical simulations by Lev Arzamasskiy of the Institute of Advanced Study in Princeton, New Jersey, and his colleagues [1] shed new light on magnetized kinetic turbulence in such plasmas.

A new quantum approach to solve electronic structures of complex materials

If you know the atoms that compose a particular molecule or solid material, the interactions between those atoms can be determined computationally, by solving quantum mechanical equations—at least, if the molecule is small and simple. However, solving these equations, critical for fields from materials engineering to drug design, requires a prohibitively long computational time for complex molecules and materials.

Now, researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Chicago’s Pritzker School of Molecular Engineering (PME) and Department of Chemistry have explored the possibility of solving these electronic structures using a quantum .

The research, which uses a combination of new computational approaches, was published online in the Journal of Chemical Theory and Computation. It was supported by Q-NEXT, a DOE National Quantum Information Science Research Center led by Argonne, and by the Midwest Integrated Center for Computational Materials (MICCoM).