Two Amazon papers at #QIP2022 could have near-term applications: Mario Berta and colleagues propose a new approach to statistical phase estimation that could en… See more.
New phase estimation technique reduces qubit count, while learning framework enables characterization of noisy quantum systems.
For all his genius, he had his tendency to be stuck in his ways — whether black holes, quantum mechanics, or flip-flopping on gravitational waves.
How can Einstein’s theory of gravity be unified with quantum mechanics? It is a challenge that could give us deep insights into phenomena such as black holes and the birth of the universe. Now, a new article in Nature Communications, written by researchers from Chalmers University of Technology, Sweden, and MIT, U.S., presents results that cast new light on important challenges in understanding quantum gravity.
A grand challenge in modern theoretical physics is to find a “unified theory” that can describe all the laws of nature within a single framework—connecting Einstein’s general theory of relativity, which describes the universe on a large scale, and quantum mechanics, which describes our world at the atomic level. Such a theory of “quantum gravity” would include both a macroscopic and microscopic description of nature.
“We strive to understand the laws of nature and the language in which these are written is mathematics. When we seek answers to questions in physics, we are often led to new discoveries in mathematics too. This interaction is particularly prominent in the search for quantum gravity—where it is extremely difficult to perform experiments,” explains Daniel Persson, Professor at the Department of Mathematical Sciences at Chalmers university of technology.
If true, Redmond is capable sustaining a stable working environment somewhere after all.
The field of machine learning on quantum computers got a boost from new research removing a potential roadblock to the practical implementation of quantum neural networks. While theorists had previously believed an exponentially large training set would be required to train a quantum neural network, the quantum No-Free-Lunch theorem developed by Los Alamos National Laboratory shows that quantum entanglement eliminates this exponential overhead.
“Our work proves that both big data and big entanglement are valuable in quantum machine learning. Even better, entanglement leads to scalability, which solves the roadblock of exponentially increasing the size of the data in order to learn it,” said Andrew Sornborger, a computer scientist at Los Alamos and a coauthor of the paper published Feb. 18 in Physical Review Letters. “The theorem gives us hope that quantum neural networks are on track towards the goal of quantum speed-up, where eventually they will outperform their counterparts on classical computers.”
The classical No-Free-Lunch theorem states that any machine-learning algorithm is as good as, but no better than, any other when their performance is averaged over all possible functions connecting the data to their labels. A direct consequence of this theorem that showcases the power of data in classical machine learning is that the more data one has, the better the average performance. Thus, data is the currency in machine learning that ultimately limits performance.
In the last decades of his life, Albert Einstein hoped to unite his description of gravity with existing models of electromagnetism under a single master theory.
It’s a quest that continues to vex theoretical physicists to this day. Two of our best models of reality – Einstein’s general theory of relativity and the laws of quantum mechanics – are as immiscible as oil and water.
Whatever a combination of the two looks like, it will almost certainly reveal foundations to the Universe quite unlike anything we can visualize.
Probability of a reaction occurring increases 100-fold and points to quantum control of chemistry.
A new step towards quantum control of chemistry has been achieved by researchers in the US, who found that tuning the magnetic field applied to colliding ultracold molecules could alter the probability of them reacting or undergoing inelastic scattering a 100-fold.1 The work could potentially prove useful for producing large ensembles of molecules in the same state and investigating their properties.
At room temperature, the random thermal motion of atoms and molecules blurs the quantum nature of chemistry. In an ultracold regime, however, this thermal motion is stilled, revealing chemical interactions as quantum interference processes between matter waves. Remarkable phenomena have been seen in ultracold atomic gases, such as the creation of Bose–Einstein condensates, in which atoms all enter the quantum ground state of a trap, allowing a macroscopic view of their quantum wavefunction. Wolfgang Ketterle at the Massachusetts Institute of Technology (MIT), whose group performed the new research, shared the 2001 physics Nobel prize for the creation of this condensate.
Cooling molecules to the ground state of a trap is much trickier than cooling atoms because they can contain thermal energy in so many internal degrees of freedom, and was only achieved by Jun Ye of JILA in the US and colleagues recently.2 In 2020, Ye’s group applied an electric field to potassium–rubidium molecules, which decay into diatomic potassium and rubidium molecules. The researchers showed that, at a specific field, the molecules were excited into states forbidden by quantum mechanics and could get close enough to react. This drastically slowed the decay rate. ‘For our system, we typically think that, if the two molecules get very close together, there is close to a 100% chance that they will undergo a chemical reaction,’ explains Kyle Matsuda, Ye’s PhD student and the 2020 paper’s lead author.
A mathematical analysis helps illuminate the puzzle over how information escapes from a black hole.
A RIKEN physicist and two colleagues have found that a wormhole—a bridge connecting distant regions of the Universe—helps to shed light on the mystery of what happens to information about matter consumed by black holes.
Einstein’s theory of general relativity predicts that nothing that falls into a black hole can escape its clutches. But in the 1970s, Stephen Hawking calculated that black holes should emit radiation when quantum mechanics, the theory governing the microscopic realm, is considered. “This is called black hole evaporation because the black hole shrinks, just like an evaporating water droplet,” explains Kanato Goto of the RIKEN Interdisciplinary Theoretical and Mathematical Sciences.
Identifying the shape of massive astronomical object is not a simple task. Even with recent observations of gravitational waves the mass and angular momentum of the object remain known with large uncertainty. Moreover, it exists exotic objects, as wormholes who can mimic the shape of black holes for example. The gravitational spectrum of wormholes has a wide range of interpretations. A current challenge addressed by researcher R. A. Konoplya consists of mathematically describing wormholes in order to be able to eventually identify them in the space.
According to current theory a wormhole is a theoretical passage through space-time that could create shortcuts in the universe. The original wormhole solution was discovered by Einstein and Rosen (ER) in 1935 and later John Wheeler has shown their importance in quantum gravity. It was then discovered that it was possible to construct “traversable” wormhole solutions since the ER=EPR proposal. It also appears the quantum fluctuations of the space-time are such that a tiny wormhole could connect Planckian pixel with the entanglement mechanism of quantum space-time itself.
Time only moves forward—or does it?
Physicists refer to this idea as the “arrow of time,” and the idea of unidirectional time seems to hold true for life and objects on a human scale. But on a quantum scale, things seem to work differently, even strangely.
For physicists, the arrow of time is dictated by the second law of thermodynamics, which says that disorder (or entropy) increases over time. The transfer of heat is a perfect example of this. On a chilly day, you’d expect your coffee to get colder if the air around it is cooler. Heat scatters in the presence of lower temperatures; it doesn’t concentrate.
