The stunning experiment, which reconstructs the properties of entangled photons from a 2D interference pattern, could be used to design faster quantum computers.
Category: quantum physics – Page 381
Why Is 1/137 One of the Greatest Unsolved Problems In Physics?
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.
Check out the Space Time Merch Store.
https://www.pbsspacetime.com/shop.
Sign up for the mailing list to get episode notifications and hear special announcements!
Gambling Meets Quantum Physics — New “Bandit” Algorithm Uses Light for Better Bets
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.
Scientists develop fermionic quantum processor
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.
Scientists develop fermionic quantum processor
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 quantum state simultaneously. This makes them ideal for simulating systems where fermionic statistics play a crucial role, such as molecules, superconductors and quark-gluon plasmas.
Before the Big Bang 11: Did the Universe Create itself? The PTC model
What happened before the Big Bang? In two of our previous films we examined cyclic cosmologies and time travel universe models. Specially, the Gott and Li Model https://www.youtube.com/watch?v=79LciHWV4Qs) and Penrose’s Conformal Cyclic Cosmology https://www.youtube.com/watch?v=FVDJJVoTx7s). Recently Beth Gould and Niayesh Afshordi of the Perimeter Institute for Theoretical Physics have fused these two models together to create a startling new vision of the universe. In this film they explain their new proposal, known as Periodic Time Cosmology.
0:00 Introduction.
0:45 NIayesh’s story.
1:15 Beth’s story.
2:25 relativity.
3:26 Gott & Li model.
6:23 origins of the PTC model.
8:17 PTC periodic time cosmology.
10:55 Penrose cyclic model.
13:01 Sir Roger Penrose.
14:19 CCC and PTC
15:45 conformal rescaling and the CMB
17:28 assumptions.
18:41 why a time loop?
20:11 empirical test.
23:96 predcitions.
26:19 inflation vs PTC
30:22 gravitational waves.
31:40 cycles and the 2nd law.
32:54 paradoxes.
34:08 causality.
35:17 immortality in a cyclic universe.
38:02 eternal return.
39:21 quantum gravity.
39:57 conclusion.
Elizabeth Gould has asked to make this clarification in the written text ” “Despite the availability of infinite time in the periodic time model, this doesn’t lead to thermalization in a typical time-evolution scenario, and therefore doesn’t, strictly speaking, solve the problem related to thermalization in the power spectrum. The reason for this is that, unlike bounce models with a net expansion each cycle, our model has an effective contraction during the conformal phases. Periodic time, therefore, has a unique character in which it reuses the power spectrum from the previous cycles, which is confined to a given form due to the constraints of the system, rather than removing the old power spectrum and needing to produce a new one.”
Microsoft Wants to Build a Quantum Supercomputer Within a Decade
Since the start of the quantum race, Microsoft has placed its bets on the elusive but potentially game-changing topological qubit. Now the company claims its Hail Mary has paid off, saying it could build a working processor in less than a decade.
Today’s leading quantum computing companies have predominantly focused on qubits—the quantum equivalent of bits—made out of superconducting electronics, trapped ions, or photons. These devices have achieved impressive milestones in recent years, but are hampered by errors that mean a quantum computer able to outperform classical ones still appears some way off.
Microsoft, on the other hand, has long championed topological quantum computing. Rather than encoding information in the states of individual particles, this approach encodes information in the overarching structure of the system. In theory, that should make the devices considerably more tolerant of background noise from the environment and therefore more or less error-proof.
An IBM Quantum Computer Beat a Supercomputer in a Benchmark Test
The teams pitted IBM’s 127-qubit Eagle chip against supercomputers at Lawrence Berkeley National Lab and Purdue University for increasingly complex tasks. With easier calculations, Eagle matched the supercomputers’ results every time—suggesting that even with noise, the quantum computer could generate accurate responses. But where it shone was in its ability to tolerate scale, returning results that are—in theory—far more accurate than what’s possible today with state-of-the-art silicon computer chips.
At the heart is a post-processing technique that decreases noise. Similar to looking at a large painting, the method ignores each brush stroke. Rather, it focuses on small portions of the painting and captures the general “gist” of the artwork.
The study, published in Nature, isn’t chasing quantum advantage, the theory that quantum computers can solve problems faster than conventional computers. Rather, it shows that today’s quantum computers, even when imperfect, may become part of scientific research—and perhaps our lives—sooner than expected. In other words, we’ve now entered the realm of quantum utility.