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Category: quantum physics

Quantum algorithm beats classical tools on complement sampling tasks

Quantum computers—devices that process information using quantum mechanical effects—have long been expected to outperform classical systems on certain tasks. Over the past few decades, researchers have worked to rigorously demonstrate such advantages, ideally in ways that are provable, verifiable and experimentally realizable.

A team of researchers working at Quantinuum in the United Kingdom and QuSoft in the Netherlands has now developed a quantum algorithm that solves a specific sampling task—known as complement sampling—dramatically more efficiently than any classical algorithm. Their paper, published in Physical Review Letters, establishes a provable and verifiable quantum advantage in sample complexity: the number of samples required to solve a problem.

“We stumbled upon the core result of this work by chance while working on a different project,” Harry Buhrman, co-author of the paper, told Phys.org. “We had a set of items and two quantum states: one formed from half of the items, the other formed from the remaining half. Even though the two states are fundamentally distinct, we showed that a quantum computer may find it hard to tell which one it is given. Surprisingly, however, we then realized that transforming one state into the other is always easy, because a simple operation can swap between them.”

Quantum computers go high-dimensional with a four-state photon gate

The collaboration of TU Wien with research groups in China has resulted in a crucial building block for a new kind of quantum computer: The realization of a novel type of quantum logic gate makes it possible to carry out quantum computations on pairs of photons that are each in four different quantum states, or combinations thereof. The advancement is an important milestone for optical quantum computers. The study has now been published in Nature Photonics.

The basic idea of quantum computers is simple: While a classical computer only works with the values “0” and “1,” quantum physics allows for arbitrary combinations of these states. In a certain sense, a quantum bit (“qubit”) can be in the states 0 and 1 simultaneously. This makes it possible to develop algorithms that can solve some problems much faster than a comparable classical computer.

However, such superpositions can in principle involve more than two states. Depending on what degree of freedom one considers, a quantum system such as a photon may not just have two different settings—two different outcomes of a potential measurement—but many. In this case, one refers to the system as a “qudit” rather than a “qubit.”

How to improve the performance of qubits: Super-fast fluctuation detection achieved

Using commercially available technology and innovative methods, researchers at NBI have pushed the limits of how fast you can detect changes in the sensitive quantum states in the qubit. Their work allows researchers to follow rapid changes in qubit performance that were previously invisible. The study is published in the journal Physical Review X.

The workhorse of any quantum-based application aimed at the coveted, but not yet fully realized quantum computer is the qubit. It is, however, a rather fragile workhorse.

Qubits, and quantum processors in general, are highly sensitive to their environment. Typically, the materials in which they are embedded contain microscopic defects that are still not fully understood. These defects can spatially fluctuate extremely fast, sometimes hundreds of times per second. As they fluctuate, the rate at which a qubit loses energy, and therefore useful quantum information, also changes.

Connecting two opposite realities: How one heavy particle can reshape an entire Quantum world

Physicists have earlier debated about exotic electrons or atoms interacting with large numbers of surrounding particles. In terms of the Quasiparticle Model, a single particle travels through a sea of fermions, which include electrons, protons, or neutrons, and interacts persistently with its neighbours, according to a report in the SciTech daily.

When the particles travel, they attract neighbouring particles surrounded with it, forming an entity identified as a Fermi polaron. In fact, it reflects the coordinated motion of the impurity and the particles near it. A doctoral candidate at Heidelberg University’s Institute for Theoretical Physics, Eugen Dizer, explained that this idea has become vital for strongly interacting systems that range from ultracold atomic gases to solid materials and even nuclear matter.

Scientists Believe Quantum Computers AreAbout to Cross a Major Line

We began this inquiry by looking at the mismatch between our computers and our brains. We realized that we were trying to run biological software on the wrong hardware. That era is ending. As we refine these quantum processors, we are finally building a mirror that is accurate enough to reflect the true nature of the mind. We are not just building faster computers. We are building a vessel that can hold the physics of thought.

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Timestamps:
0:00 Quantum Computers.
1:18 The Scale Problem.
4:40 The Thermodynamic Wall.
8:11 Quantum Mechanics in Wetware.
13:58 The \

Quantum computer breakthrough tracks qubit fluctuations in real time

Researchers at the Niels Bohr Institute have significantly increased how quickly changes in delicate quantum states can be detected inside a qubit. By combining commercially available hardware with new adaptive measurement techniques, the team can now observe rapid shifts in qubit behavior that were previously impossible to see.

Qubits are the fundamental units of quantum computers, which scientists hope will one day outperform today’s most powerful machines. But qubits are extremely sensitive. The materials used to build them often contain tiny defects that scientists still do not fully understand. These microscopic imperfections can shift position hundreds of times per second. As they move, they alter how quickly a qubit loses energy and with it valuable quantum information.

Until recently, standard testing methods took up to a minute to measure qubit performance. That was far too slow to capture these rapid fluctuations. Instead, researchers could only determine an average energy loss rate, masking the true and often unstable behavior of the qubit.

Quantum reservoir computing peaks at the edge of many-body chaos, study suggests

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as weather patterns, recorded speech or stock market trends. Classical reservoir computing techniques are known to perform best at the “edge of chaos,” or in simpler terms, at a “sweet spot” in which the behavior of systems is neither entirely predictable (i.e., order) nor completely unpredictable (i.e., chaos).

In recent years, some physicists and quantum engineers have been exploring the possibility of realizing a quantum equivalent of classical reservoir computing, known as quantum reservoir computing (QRC). These approaches enable the processing of temporal data and the prediction of events unfolding over time, leveraging high-dimensional quantum states.

Researchers at the University of Tokyo carried out a study investigating how QRC would behave when applied to complex quantum many-body systems, which consist of several interacting quantum particles. Their paper, published in Physical Review Letters, introduces a physics-based framework that could inform the future development of QRC systems.

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