Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: quantum physics – Page 289

Diamond has long been the preferred material for quantum sensing, but its size limits its applications. Recent research highlights hBN’s potential as a replacement, especially after TMOS researchers developed methods to stabilize its atomic defects and study its charge states, opening doors for its integration into devices where diamond can’t fit.

Diamond has long held the crown in the realm of quantum sensing, thanks to its coherent nitrogen-vacancy centers, adjustable spin, magnetic field sensitivity, and capability to operate at room temperature. With such a suitable material so easy to fabricate and scale, there’s been little interest in exploring diamond alternatives.

However, this titan of the quantum domain has a vulnerability. It’s simply too large. Much like how an NFL linebacker isn’t the top pick for a jockey in the Kentucky Derby, diamond falls short when delving into quantum sensors and data processing. When diamonds get too small, the super-stable defect it’s renowned for begins to crumble. There is a limit at which a diamond becomes useless.

Read more | >

In their 1982 paper, Fredkin and Toffoli had begun developing their work on reversible computation in a rather different direction. It started with a seemingly frivolous analogy: a billiard table. They showed how mathematical computations could be represented by fully reversible billiard-ball interactions, assuming a frictionless table and balls interacting without friction.

This physical manifestation of the reversible concept grew from Toffoli’s idea that computational concepts could be a better way to encapsulate physics than the differential equations conventionally used to describe motion and change. Fredkin took things even further, concluding that the whole Universe could actually be seen as a kind of computer. In his view, it was a ‘cellular automaton’: a collection of computational bits, or cells, that can flip states according to a defined set of rules determined by the states of the cells around them. Over time, these simple rules can give rise to all the complexities of the cosmos — even life.

He wasn’t the first to play with such ideas. Konrad Zuse — a German civil engineer who, before the Second World War, had developed one of the first programmable computers — suggested in his 1969 book Calculating Space that the Universe could be viewed as a classical digital cellular automaton. Fredkin and his associates developed the concept with intense focus, spending years searching for examples of how simple computational rules could generate all the phenomena associated with subatomic particles and forces3.

Read more | >

• Encryption and segmentation: These operate on the assumption some fraction of the network is already compromised. Restricting the reach and utility of any captured data and accessible networks will mitigate the damage even on breached systems.

• SBOM documentation: Regulatory compliance can be driven by industry organizations and the government, but it will take time to establish standards. SBOM documentation is an essential foundation for best practices.

If “democracy dies in darkness,” and that includes lies of omission in reporting, then cybersecurity suffers the same fate with backdoors. The corollary is “don’t roll your own crypto” even if well-intentioned. The arguments for weakening encryption to make law enforcement easier falls demonstrably flat, with TETRA just the latest example. Secrets rarely stay that way forever, and sensitive data is more remotely accessible than at any time in history. Privacy and global security affect us all, and the existence of these single points of failure in our cybersecurity efforts are unsustainable and will have unforeseeable consequences. We need to innovate and evolve the internet away from this model to have durable security assurances.

Read more | >

Thank you to Squarespace for supporting PBS. Go to https://www.squarespace.com/pbs for a free trial, and when you are ready to launch, go to Squarespace.com/PBS to save 10% off your first purchase of a website or domain.

PBS Member Stations rely on viewers like you. To support your local station, go to: http://to.pbs.org/DonateSPACE

Sign Up on Patreon to get access to the Space Time Discord!
https://www.patreon.com/pbsspacetime.

The Fine Structure Constant is one the strangest numbers in all of physics. It’s the job of physicists to worry about numbers, but there’s one number that physicists have stressed about more than any other. That number is 0.00729735256 — approximately 1/137. This is the fine structure constant, and it appears everywhere in our equations of quantum physics, and we’re still trying to figure out why.

Continue reading “Why Is 1/137 One of the Greatest Unsolved Problems In Physics?” | >

How does a gambler maximize winnings from a row of slot machines? This question inspired the “multi-armed bandit problem,” a common task in reinforcement learning in which “agents” make choices to earn rewards. Recently, an international team of researchers, led by Hiroaki Shinkawa from the University of Tokyo, introduced an advanced photonic reinforcement learning method that transitions from the static bandit problem to a more intricate dynamic setting. Their findings were recently published in the journal, Intelligent Computing.

The success of the scheme relies on both a photonic system to enhance the learning quality and a supporting algorithm. Looking at a “potential photonic implementation,” the authors developed a modified bandit Q-learning algorithm and validated its effectiveness through numerical simulations. They also tested their algorithm with a parallel architecture, where multiple agents operate at the same time, and found that the key to accelerating the parallel learning process is to avoid conflicting decisions by taking advantage of the quantum interference of photons.

Although using the quantum interference of photons is not new in this field, the authors believe this study is “the first to connect the notion of photonic cooperative decision-making with Q-learning and apply it to a dynamic environment.” Reinforcement learning problems are generally set in a dynamic environment that changes with the agents’ actions and are thus more complex than the static environment in a bandit problem.

Read more | >

Fermionic atoms adhere to the Pauli exclusion principle, preventing more than one from simultaneously being in the same quantum state. As a result, they are perfect for modeling systems like molecules, superconductors, and quark-gluon plasmas where fermionic statistics are critical.

Using fermionic atoms, scientists from Austria and the USA have designed a new quantum computer to simulate complex physical systems. The processor uses programmable neutral atom arrays and has hardware-efficient fermionic gates for modeling fermionic models.

The group, under the direction of Peter Zoller, showed how the new quantum processor can simulate fermionic models from quantum chemistry and particle physics with great accuracy.

Read more | >

Researchers from Austria and the U.S. have designed a new type of quantum computer that uses fermionic atoms to simulate complex physical systems. The processor uses programmable neutral atom arrays and is capable of simulating fermionic models in a hardware-efficient manner using fermionic gates.

The team led by Peter Zoller demonstrated how the new quantum processor can efficiently simulate fermionic models from quantum chemistry and particle physics. The paper is published in the journal Proceedings of the National Academy of Sciences.

Fermionic atoms are atoms that obey the Pauli exclusion principle, which means that no two of them can occupy the same simultaneously. This makes them ideal for simulating systems where fermionic statistics play a crucial role, such as molecules, superconductors and quark-gluon plasmas.

Read more | >