Category: Physics

Manuel Endres, professor of physics at Caltech, specializes in finely controlling single atoms using devices known as optical tweezers. He and his colleagues use the tweezers, made of laser light, to manipulate individual atoms within an array of atoms to study fundamental properties of quantum systems. Their experiments have led to, among other advances, new techniques for erasing errors in simple quantum machines; a new device that could lead to the world’s most precise clocks; and a record-breaking quantum system controlling more than 6,000 individual atoms.

One nagging factor in this line of work has been the normal jiggling motion of atoms, which make the systems harder to control. Now, reporting in the journal Science, the team has flipped the problem on its head and used this atomic motion to encode quantum information.

“We show that atomic motion, which is typically treated as a source of unwanted noise in quantum systems, can be turned into a strength,” says Adam Shaw, a co-lead author on the study along with Pascal Scholl and Ran Finkelstein.

Shaw was formerly a graduate student at Caltech during these experiments and is now a postdoctoral scholar at Stanford University. Scholl served as a postdoc at Caltech and is now working at the quantum computing company Pasqal. Finkelstein held the Troesh Postdoctoral Prize Fellowship at Caltech and is now a professor at Tel Aviv University.

Ultimately, the experiment not only encoded quantum information in the motion of the atoms but also led to a state known as hyper-entanglement. In basic entanglement, two particles remain connected even when separated by vast distances. When researchers measure the particles’ states, they observe this correlation: For example, if one particle is in a state known as spin up (in which the orientation of the angular momentum is pointing up), the other will always be spin down.

In hyper-entanglement, two characteristics of a particle pair are correlated. As a simple analogy, this would be like a set of twins separated at birth having both the same names and same types of cars: The two traits are correlated between the twins.

In the new study, Endres and his team were able to hyper-entangle pairs of atoms such that their individual states of motion and their individual electronic states—their internal energy levels—were correlated among the atoms. What is more, this experimental demonstration implies that even more traits could be entangled at the same time.

“This allows us to encode more quantum information per atom,” Endres explains. “You get more entanglement with fewer resources.”

The experiment is the first demonstration of hyper-entanglement in massive particles, such as neutral atoms or ions (earlier demonstrations used photons).

Adam Shaw, Ivaylo Madjarov and Manuel Endres work on their laser-based apparatus at Caltech. Credit: Caltech
For these experiments, the team cooled down an array of individual alkaline-earth neutral atoms confined inside optical tweezers. They demonstrated a novel form of cooling via “detection and subsequent active correction of thermal motional excitations,” says Endres, which he compares to James Clerk Maxwell’s famous 1867 thought experiment invoking a demon that measures and sorts particles in a chamber. “We essentially measure the motion of each atom and apply an operation depending on the outcome, atom-by-atom, similar to Maxwell’s demon.”

The method, which outperformed the best-known laser cooling techniques, caused the atoms to come to nearly a complete standstill.

From there, the researchers induced the atoms to oscillate like a swinging pendulum, but with an amplitude of approximately100 nanometers, which is much smaller than the width of a human hair. They were able to excite the atoms into two distinct oscillations simultaneously, causing the motion to be in a state of superposition. Superposition is a quantum state in which a particle exhibits opposite traits simultaneously, like a particle’s spin being both up and down at the same time.

“You can think of an atom moving in this superposition state like a kid on a swing who starts getting pushed by two parents on opposite sides, but simultaneously,” Endres says. “In our everyday world, this would certainly lead to a parental conflict; in the quantum world, we can remarkably make use of this.”

They then entangled the individual, swinging atoms to partner atoms, creating a correlated state of motion over several micrometers of distance. After the atoms were entangled, the team then hyper-entangled them in such a way that both the motion and the electronic states of the atoms were correlated.

“Basically, the goal here was to push the boundaries on how much we could control these atoms,” Endres says. “We are essentially building a toolbox: We knew how to control the electrons within an atom, and we now learned how to control the external motion of the atom as a whole. It’s like an atom toy that you have fully mastered.”

The findings could lead to new ways to perform quantum computing as well as quantum simulations designed to probe fundamental questions in physics. “Motional states could become a powerful resource for quantum technology, from computing to simulation to precision measurements,” Endres says.

When two-dimensional electron systems are subjected to magnetic fields at low temperatures, they can exhibit interesting states of matter, such as fractional quantum Hall liquids. These are exotic states of matter characterized by fractionalized excitations and the emergence of interesting topological phenomena.

Researchers at Cavendish Laboratory and Massachusetts Institute of Technology (MIT) set out to better understand these fascinating states using machine learning, specifically employing a newly developed attention-based fermionic neural network (FNN).

The method they developed, outlined in a paper published in Physical Review Letters, was trained to find the lowest-energy quantum state (i.e., ground state) of fractional quantum Hall liquids.

“AI has transformed many areas of society and science, but we are yet to see an AI breakthrough in quantum physics,” Liang Fu, co-author of the paper, told Phys.org.

“Solving quantum many-body problems is known to be extremely difficult, because a quantum system can be in a superposition of exponentially many states: literally, everything everywhere all at once! So, we wanted to find out whether AI has the power to conquer the quantum world.”

The main objective of the recent research by Fu and his colleagues was to assess the potential of advanced machine learning tools for solving complex quantum problems. Working towards this goal, the researchers developed a new FNN and tried to use it to uncover the hidden patterns of electrons in topological quantum liquids.

“Our recent paper was inspired by the rapid development of AI, in particular the FNN, to tackle quantum chemistry problems,” said Yi Teng, co-author of the paper. “We wanted to demonstrate that this neural network based variational approach can also be applied to complex condensed matter systems, proven challenging for traditional numerical methods.”

Fractional quantum Hall liquids are intricate states of matter known to emerge in 2D electron systems when a strong magnetic field is applied to them. The computational method developed by Fu, Teng and Dai can capture rich physical phenomena, successfully uncovering microscopic features of fermionic quantum Hall liquids and competing states.

“The fractional quantum Hall liquid hosts emergent particles—-neither bosons nor fermions—-that carry a quantized fraction of electron’s charge,” explained Fu. “While great success in this venerable field came from the best human minds, there remain long-standing open questions that require numerically accurate solutions beyond the capability of traditional methods. So, we gave AI a shot.”

This study is among the first to demonstrate the potential of AI and machine learning for studying fractional phases of matter. Using their FNN, Fu, Teng and Dai generated a variational ansatz, which is a flexible mathematical structure that can be optimized to estimate a system’s ground state.

“We then used Monte-Carlo sampling to minimize the total energy in search of ground state,” said Teng. “We also performed extensive benchmarks and found neural networks consistently outperform traditional methods. The biggest advantage of our method is that no human biases are put in by hand, and the neural network captures all possible states of electrons without truncating the Hilbert space.”

The team’s demonstration highlights the promise of FNNs for the study and estimation of states that can be difficult to predict theoretically. As part of their study, the researchers successfully used their FNN to accurately predict the transition of a 2D electron system from liquid to crystal.

“We demonstrate that an unbiased neural network can be used to solve different phases (fractional quantum Hall liquid and Wigner crystal in our case) in a unified manner with unprecedented accuracy,” said Teng. “This shows the capacity and versality of the NN-based variational method in quantum condensed matter physics.”

In the future, the model developed by Fu, Teng and Dai could be improved further and used to predict the quantum phase diagram of various 2D electron systems. In addition, it could inspire the development of other FNN-based models for quantum research and could potentially contribute to the discovery of new quantum states of matter.

“For me, this project was a mind-blowing experience,” said Fu. “I am now fully convinced of the transformative power of AI for quantum science, offering a vast opportunity.

“Looking ahead, I also believe that solving challenging quantum problems provides an objective benchmark for different large language model architectures. Think of it: no training data is involved in such test, and the ranking is objectively determined by the variational energy. The best of all is the reward—AI solving the quantum phase diagram of real materials and discovering new quantum states of matter.”

As part of their future studies, the researchers plan to use their FNN-based method to study a wide range of other quantum systems. For instance, they would like to use it to gather new insights into non-Abelian states, unconventional superconductivity and quantum spin liquids.

“Going forward, I’m also excited to both use AI to solve challenging physics problems, and to use challenging physics problems to learn more about AI,” added David Dai, co-author of the paper.

When most people think of crystals, they picture suncatchers that act as rainbow prisms or the semi-transparent stones that some believe hold healing powers. However, to scientists and engineers, crystals are a form of materials in which their constituents—atoms, molecules, or nanoparticles—are arranged regularly in space. In other words, crystals are defined by the regular arrangement of their constituents. Common examples are diamonds, table salt, or sugar cubes.

However, in research just published in Soft Matter, a team led by Rensselaer Polytechnic Institute’s Sangwoo Lee, associate professor in the Department of Chemical and Biological Engineering, discovered that crystal structures are not necessarily always regularly arranged. The discovery advances the field of materials science and has unrealized implications for the materials used for semiconductors, solar panels, and electric vehicle technologies.

One of the most common and important classes of crystal structures is the close-packed structures of regular spheres constructed by stacking layers of spheres in a honeycomb arrangement. There are many ways to stack the layers to construct close-packed structures, and how nature selects specific stacking is an important question in materials and physics research. In the close-packing construction, there is a very unusual structure with irregularly spaced constituents known as the random stacking of two-dimensional hexagonal layers (RHCP). This structure was first observed from cobalt metal in 1942, but it has been regarded as a transitional and energetically unpreferred state.

Lee’s research group collected X-ray scattering data from soft model nanoparticles made of polymers and realized that the scattering data contains important results about RHCP but is very complicated. Then, Patrick Underhill, professor in Rensselaer’s Department of Chemical and Biological Engineering, enabled the analysis of the scattering data using the supercomputer system, Artificial Intelligence Multiprocessing Optimized System (AiMOS), at the Center for Computational Innovations.

“What we found is that the RHCP structure is, very likely, a stable structure, and this is the reason that RHCP has been widely observed in many materials and naturally occurring crystal systems,” said Lee. “This finding challenges the classical definition of crystals.”

The study provides insights into the phenomenon known as polytypism, which enables the formation of RHCP and other close-packed structures. A representative material with polytypism is silicon carbide, widely used for high-voltage electronics in electric vehicles and as hard materials for body armor. Lee’s team’s findings indicate that those polytypic materials may have continuous structural transitions, including the non-classical random arrangements with new useful properties.

“The problem of how soft particles pack seems straightforward, but even the most basic questions are challenging to answer,” said Kevin Dorfman of the University of Minnesota-Twin Cities, who is unaffiliated with this research. “This paper provides compelling evidence for a continuous transition between face-centered cubic (FCC) and hexagonal close-packed (HCP) lattices, which implies a stable random hexagonal close-packed phase between them, and thus makes an important breakthrough in materials science.”

“I am particularly pleased with this discovery, which shows the power of advanced computation to make an important breakthrough in materials science by decoding the molecular level structures in soft materials,” said Shekhar Garde, dean of Rensselaer’s School of Engineering. “Lee and Underhill’s work at Rensselaer also promises to open up opportunities for many technological applications for these new materials.”

Lee and Underhill were joined in research by Rensselaer’s Juhong Ahn, Liwen Chen of the University of Shanghai for Science and Technology, and Guillaume Freychet and Mikhail Zhernenkov of Brookhaven National Laboratory.

More information: Juhong Ahn et al, Continuous transition of colloidal crystals through stable random orders, Soft Matter (2023). DOI: 10.1039/D3SM00199G

Journal information: Soft Matter 

Provided by Rensselaer Polytechnic Institute 

An international team of researchers including scientists from FAU has, for the first time, used X-rays for an imaging technique that exploits a particular quantum characteristic of light. In their article, which has now been published in the journal Physical Review Letters, the researchers detail how this process could be used for imaging non-crystallized macromolecules.

The research team used the extremely short and very intensive X-ray pulses at the X-ray laser European EXFEL in Hamburg in order to generate fluorescence photons that arrived almost simultaneously at the detector—in a time window of less than one femtosecond (one quadrillionth of a second). By calculating the photon-photon correlations in the fluorescence of the illuminated copper atoms, it was possible to create an image of the light source.

On the atomic scale, the structures of materials and macromolecules are usually determined using X-ray crystallography. While this technique relies on coherent X-ray diffraction, the scattering of X-ray light can cause incoherent processes such as fluorescence emissions, which can dominate, even though they do not make a useful contribution to the diffraction measurement. Instead, they add a functionless haze or background to the measurement data.

As long ago as the 1950s, two British astronomers proved that it is possible to gain structural information from such self-luminous light sources, in their case it was the light from stars. Robert Hanbury Brown and Richard Twiss, whose method is known as intensity interferometry, opened a new door to the understanding of light and founded the field of quantum optics.

Recently, scientists from FAU, the Max Planck Institute for the Structure and Dynamics of Matter and the Deutsches Elektronen-Synchrotron (DESY) suggested that intensity interferometry could be adapted for atomic-resolution imaging using X-ray fluorescence. The challenge in extending this idea to X-rays is that the coherence time of the photons, which dictates the time interval available to perform photon–photon correlations, is extremely short. It is determined by the radiative decay time of the excited atom, which is about 0.6 femtoseconds for copper atoms.

Together with scientists from Uppsala University and the European XFEL, the group has now overcome that challenge by using femtosecond-duration XFEL pulses from that facility to initiate X-ray fluorescence photons within the coherence time. The team generated a source consisting of two fluorescing spots in a foil of copper and measured the fluorescence on a million-pixel detector placed eight meters away.

Only about 5,000 photons were detected on each illumination pulse, and the cumulative sum over 58 million pulses produced just a featureless uniform distribution. However, when the researchers instead summed photon-photon correlations across all images from the detector, a striped pattern emerged, which was analyzed like a coherent wave field to reconstruct an image of the fluorescent source, consisting of two well-separated spots of light.

The scientists now hope to combine this new method with conventional X-ray diffraction to image single molecules. Element-specific fluorescent light could expose substructures that are specific to certain atoms and even to certain chemical states. This could contribute to a better understanding of the functions of important enzymes such as those involved in photosynthesis.

More information: Fabian Trost et al, Imaging via Correlation of X-Ray Fluorescence Photons, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.130.173201

Journal information: Physical Review Letters 

Provided by Friedrich–Alexander University Erlangen–Nurnberg 

Better understanding the formation of swirling, ring-shaped disturbances—known as vortex rings—could help nuclear fusion researchers compress fuel more efficiently, bringing it closer to becoming a viable energy source.

The model developed by researchers at the University of Michigan could aid in the design of the fuel capsule, minimizing the energy lost while trying to ignite the reaction that makes stars shine. In addition, the model could help other engineers who must manage the mixing of fluids after a shock wave passes through, such as those designing supersonic jet engines, as well as physicists trying to understand supernovae.

“These vortex rings move outward from the collapsing star, populating the universe with the materials that will eventually become nebulae, planets and even new stars—and inward during fusion implosions, disrupting the stability of the burning fusion fuel and reducing the efficiency of the reaction,” said Michael Wadas, a doctoral candidate in mechanical engineering at U-M and corresponding author of the study.

“Our research, which elucidates how such vortex rings form, can help scientists understand some of the most extreme events in the universe and bring humanity one step closer to capturing the power of nuclear fusion as an energy source,” he said.

Nuclear fusion pushes atoms together until they merge. This process releases several times more energy than breaking atoms apart, or fission, which powers today’s nuclear plants. Researchers can create this reaction, merging forms of hydrogen into helium, but at present, much of the energy used in the process is wasted.

Part of the problem is that the fuel can’t be neatly compressed. Instabilities cause the formation of jets that penetrate into the hotspot, and the fuel spurts out between them—Wadas compared it to trying to squish an orange with your hands, how juice would leak out between your fingers.

Vortex rings that form at the leading edge of these jets, the researchers have shown, are mathematically similar to smoke rings, the eddies behind jellyfish and the plasma rings that fly off the surface of a supernova.

Perhaps the most famous approach to fusion is a spherical array of lasers all pointing toward a spherical capsule of fuel. This is how experiments are set up at the National Ignition Facility, which has repeatedly broken records for energy output in recent years.

The energy from the lasers vaporizes the layer of material around the fuel—a nearly perfect, lab-grown shell of diamond in the latest record-setter in December 2022. When that shell vaporizes, it drives the fuel inward as the carbon atoms fly outward. This generates a shockwave, which pushes the fuel so hard that the hydrogen fuses.

While the spherical fuel pellets are some of the most perfectly round objects humans have ever made, each has a deliberate flaw: a fill tube, where the fuel enters. Like a straw stuck in that crushed orange, this is the most likely place for a vortex-ring-led jet to form when the compression starts, the researchers explained.

“Fusion experiments happen so fast that we really only have to delay the formation of the jet for a few nanoseconds,” said Eric Johnsen, an associate professor of mechanical engineering at U-M, who supervised the study.

The study brought together the fluid mechanics expertise of Wadas and Johnsen as well as the nuclear and plasma physics knowledge in the lab of Carolyn Kuranz, an associate professor of nuclear engineering and radiological sciences.

“In high-energy-density physics, many studies point out these structures, but haven’t clearly identified them as vortex rings,” said Wadas.

Knowing about the deep body of research into the structures seen in fusion experiments and astrophysical observations, Wadas and Johnsen were able to draw on and extend that existing knowledge rather than trying to describe them as completely new features.

Johnsen is particularly interested in the possibility that vortex rings could help drive the mixing between heavy elements and lighter elements when stars explode, as some mixing process must have occurred to produce the composition of planets like Earth.

The model can also help researchers understand the limits of the energy that a vortex ring can carry, and how much fluid can be pushed before the flow becomes turbulent and harder to model as a result. In ongoing work, the team is validating the vortex ring model with experiments.

The research is published in the journal Physical Review Letters.

More information: Michael J. Wadas et al, Saturation of Vortex Rings Ejected from Shock-Accelerated Interfaces, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.130.194001

Journal information: Physical Review Letters 

Provided by University of Michigan 

by Chinese Academy of Sciences

Introducing light conversion materials into silicon-based photovoltaic devices is an effective way to improve their photoelectric conversion efficiency. Light conversion materials include quantum cutting materials and upconversion materials.

The purpose of introducing quantum cutting materials is to divide a short-wavelength photon into two or more photons that can join the photoelectric conversion in silicon-based photovoltaic devices. Introducing upconversion materials is done to combine two or more infrared photons into one photon that can also be used for photoelectric conversion in silicon-based photovoltaic devices.

The introduction of light conversion materials can improve photoelectric conversion efficiency without changing the performance of silicon-based solar cells themselves. This method can greatly reduce the technical difficulty of improving the efficiency of silicon-based photovoltaic systems. In addition, silicon-based photovoltaic devices are exposed to sunlight, so their temperature must be managed. Managing this temperature necessitates measuring it in advance.

However, it is possible that if three materials that can individually achieve quantum cutting, upconversion, and temperature sensing are simultaneously introduced into silicon-based solar cells, it will lead to difficulties in solar cell structure design and unnecessary increase in the product costs. Therefore, finding and developing high-performance materials that combine the above three functions is a challenge.

In a new paper published in Light: Science & Applications, researchers from the School of Science, Dalian Maritime University reports that they have achieved highly efficient photo split, nearly pure infrared upconversion emission, and suitable temperature sensing for thermal management in silicon-based solar cells by adjusting the doping concentrations of Er³⁺ and Yb³⁺ in NaY(WO₄)₂ phosphor.

The work reveals that this all-in-one material is an excellent candidate for application in silicon-based solar cells for improving their photoelectric conversion efficiency and enhancing their heat management.

An in-depth understanding of the quantum cutting mechanism is significant for designing and assessing the quantum cutting materials. However, in many cases, quantum cutting processes are complicated. In this work, the authors carefully decrypted the photo-splitting steps in Er³⁺/Yb³⁺ co-doped NaY(WO₄)₂ to assist the doping-concentration-dependent spectroscopy and fluorescence dynamics.

The team states, “Based on the optical spectroscopic analyses, the quantum cutting mechanism was discovered, and the photon splitting process includes two-step energy transfer processes, namely, ⁴S_3/2+²F_7/2 ⁴I_11/2 +²F_5/2 and ⁴I_11/2 + ²F_7/2 ⁴I_15/2 + ²F_5/2.”

The quantum cutting efficiency can be confirmed experimentally and theoretically. In the ideal case, the measured quantum cutting efficiency is also defined as the internal quantum efficiency, but it is different from the traditional definition of internal quantum efficiency. The measuring technique for the quantum efficiencies is still not satisfactory since the measuring results are complicated by too many uncontrollable factors.

Therefore, the theoretical internal quantum cutting efficiency becomes significant. The authors claim, “The quantum cutting mechanism was discovered by the optical spectroscopic analyses, and the quantum cutting efficiencies were calculated in assistance of Judd-Ofelt theory, Föster-Dexter theory, energy gap law.” The authors estimated the internal quantum cutting efficiencies for NaY(WO₄)₂: Er³⁺/Yb³⁺ by taking radiative transitions, non-radiative transitions, and energy transfers into account, and achieved an efficiency as high as 173%.

Another important point of this work is that the researchers achieved nearly pure near-infrared emission of Yb³⁺.

The team observes, “These upconversion mechanisms tell us that both Er³⁺ and Er³⁺/Yb³⁺ doped NaY(WO₄)₂ phosphors exhibit strong near-infrared emissions from ⁴I_11/2⁴I_15/2 of Er³⁺ and ²F_5/2²F_7/2 of Yb³⁺ that indicates the studied phosphors are good light conversion candidate[s] for silicon-based solar cell applications.”

More information: Duan Gao et al, Near infrared emissions from both high efficient quantum cutting (173%) and nearly-pure-color upconversion in NaY(WO4)2:Er3+/Yb3+ with thermal management capability for silicon-based solar cells, Light: Science & Applications (2024). DOI: 10.1038/s41377-023-01365-2

Provided by Chinese Academy of Sciences 

Transporting energy is costly. When a current runs through conductive materials, some of the energy is lost due to resistance as particles within the material interact—just notice the warmth from your phone or laptop. This energy loss presents a hurdle to the advancement of many technologies and scientists are searching for ways to make superconductors that eliminate resistance.

Superconductors can also provide a platform for fault-tolerant quantum computing if endowed with topological properties. An example of the latter is the quantum Hall effect where the topology of electrons leads to universal, “quantized,” resistance with accuracy up to one part in a billion, which finds uses in meteorology. Unfortunately, the quantum Hall effect requires extremely strong magnetic fields, typically detrimental to superconductivity. This makes the search for topological superconductors a challenging task.

In two new papers in Physical Review Letters and Physical Review B UConn Physicist Pavel Volkov and his colleagues propose how to experimentally manipulate the quantum particles, called quasiparticles, in very thin layers of ordinary superconductors to create topological superconductors by slightly twisting the stacked layers.

Volkov explains there is a lot of research being done on ways to engineer materials by stacking layers of two-dimensional materials together:

“Most famously, this has been done with graphene. Stacking two graphene layers in a particular way results in a lot of interesting new phenomena. Some parallel those in high-temperature superconductors, which was unexpected because, by itself, graphene is not superconducting.”

Superconductivity happens when a material conducts current without any resistance or energy loss. Since resistance is a challenge for many technologies, superconducting materials have the potential to revolutionize how we do things, from energy transmission to quantum computing to more efficient MRI machines.

However, endowing superconductors with topological properties is challenging, says Volkov, and as of now, there are no materials that can reliably perform as topological superconductors.

The researchers theorize that there is an intricate relation between what happens inside the twisted superconductor layers and a current applied between them. Volkov says the application of a current makes the quasiparticles in the superconductor behave as if they were in a topological superconductor.

“The twist is essentially determining the properties, and funnily enough, it gives you some very unexpected properties. We thought about applying twisting to materials that have a peculiar form of superconductivity called nodal superconductivity,” says Volkov.

“Fortunately for us, such superconductors exist and, for example, the cuprate high-temperature superconductors are nodal superconductors. What we claim is that if you apply a current between two twisted layers of such superconductors, it becomes a topological superconductor.”

The proposal for current-induced topological superconductivity is, in principle, applicable at any twist angle, Volkov explains, and there is a wide range of angles that optimize the characteristics, which is unlike other materials studied so far.

“This is important because, for example, in twisted bilayer graphene, observation of interesting new phenomena requires to align the two layers to 1.1 degrees and deviations by .1 degrees are strongly detrimental. That means that one is required to make a lot of samples before finding one that works. For our proposal this problem won’t be as bad. If you miss the angle even by a degree, it’s not going to destroy the effect we predict.”

Volkov expects that this topological superconductor has the potential to be better than anything else currently on the market. Though one caveat is they do not know exactly what the parameters of the resulting material will be, they have estimates that may be useful for proof of principle experiments.

The researchers also found unexpected behaviors for the special value of twist angle.

“We find a particular value of the angle, the so-called ‘magic angle,’ where a new state should appear—a form of magnetism. Typically, magnetism and superconductivity are antagonistic phenomena but here, superconductivity begets magnetism, and this happens precisely because of the twisted structure of the layers.” says Volkov.

Demonstrating these predictions experimentally will bring more challenges to overcome, including making the atoms-thick layers better themselves and determining the difficult-to-measure parameters, but Volkov says there is a lot of motivation behind developing these highly complex materials.

“Basically, the main problem so far is that the candidate materials are tricky to work with. There are several groups around the world trying to do this. Monolayers of nodal superconductors, necessary for our proposal have been realized, and experiments on twisted flakes are ongoing. Yet, the twisted bilayer of these materials has not yet been demonstrated. That’s work for the future.”

These materials hold promise for improving materials we use in everyday life, says Volkov. Things already in use that take advantage of the topological states include devices used to set resistance standards with high accuracy. Topological superconductors are also potentially useful in quantum computing, as they serve as a necessary ingredient for proposals of fault-tolerant qubits, the units of information in quantum computing. Volkov also emphasizes the promise topological materials hold for precision physics,

“Topological states are useful because they allow us to do precision measurements with materials. A topological superconductor may allow us to perform such measurements with unprecedented precision for spin (magnetic moment of electron) or thermal properties.”

More information: Pavel A. Volkov et al, Current- and Field-Induced Topology in Twisted Nodal Superconductors, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.130.186001

Pavel A. Volkov et al, Magic angles and correlations in twisted nodal superconductors, Physical Review B (2023). DOI: 10.1103/PhysRevB.107.174506

Journal information: Physical Review Letters  , Physical Review B 

Provided by University of Connecticut 

Researchers at the Institute of Modern Physics (IMP) of the Chinese Academy of Sciences (CAS) and their collaborators have measured the masses of several key nuclei with high precision by employing the most advanced storage-ring mass spectrometry technique. Using the new data, they investigated X-ray bursts on the surface of a neutron star, setting constraints on the properties of neutron stars from a new perspective. The study was published in Nature Physics.

Neutron stars are considered to be the densest objects after black holes. Type-I X-ray bursts, among the brightest stellar objects frequently observed in the sky by space-based telescopes, are violent thermonuclear explosions occurring on the surfaces of neutron stars.

Due to the strong gravity of a neutron star, hydrogen- and helium-rich matter from a companion star is accreting on the surface of the neutron star for hours or days before igniting thermonuclear burning. The explosion lasts for 10 to 100 seconds, causing a bright X-ray burst. These frequent X-ray bursts offer an opportunity to study the properties of neutron stars.

The bursts are powered by a nuclear reaction sequence known as the rapid proton capture nucleosynthesis process (rp-process), which involves hundreds of exotic neutron-deficient nuclides. Among them, the waiting-point nuclides, including germanium-64, play a decisive role. “Germanium-64, like a crossroad on the path of nuclear reaction processes, is an important congested section encountered when the nuclear reaction proceeds to the medium mass region. The masses of the relevant nuclei are decisive in setting the process path and thereby the X-ray flux produced,” explained Zhou Xu, the first author of this paper and a Ph.D. student at IMP.

Therefore, precision mass measurements of the nuclei around germanium-64 are essential for understanding X-ray bursts and the properties of neutron stars. However, due to the extremely low production yield, it has been very challenging to measure the masses of these short-lived nuclei.

After more than ten years of effort, the researchers from the Storage Ring Nuclear Physics Group at IMP have developed a new ultrasensitive mass spectrometry technique at the Cooler Storage Ring (CSR) of the Heavy Ion Research Facility in Lanzhou (HIRFL), which is called Bρ-defined isochronous mass spectrometry (Bρ-IMS). It quickly and efficiently measures short-lived nuclei with extreme low production yield.

“Our experiment is capable of precisely determining the mass of a single nuclide within a millisecond after its production, and it is essentially background free in the measured spectrum,” said Prof. Wang Meng from IMP.

The researchers precisely measured the masses of arsenic-64, arsenic-65, selenium-66, selenium-67 and germanium-63. The masses of arsenic-64 and selenium-66 are the first experimental results in the world, and the mass precision of the others have all been improved. With the newly measured masses, all nuclear reaction energy related to the waiting point nucleus germanium-64 has been experimentally determined for the first time.

The researchers used the new masses as inputs for X-ray burst model calculations. They found that the new data lead to changes in the rp-process path. As a result, the X-ray burst light curve on the surface of the neutron star has an increased peak luminosity and a prolonged tail duration.

By comparing model calculations with the observed X-ray bursts of GS 1826-24, the researchers found that the distance from Earth to the burster should be increased by 6.5%, and the neutron star surface gravitational redshift coefficient needs to be reduced by 4.8% to match astronomical observations, which indicates that the density of the neutron star is lower than expected. In addition, the composition changes of the rp-process reaction products revealed that the temperature of the outer shell of the neutron star should be higher than generally believed after the X-ray burst.

The property of neutron stars is a frontier physics research topic of great importance. “Through precise nuclear mass measurement, we obtained a more accurate X-ray burst light curve on the surface of the neutron star. By comparing it with astronomical observations, we set constrains on the relationship between the mass and radius of the neutron star from a new perspective,” said Prof. Zhang Yuhu from IMP.

More information: X. Zhou et al, Mass measurements show slowdown of rapid proton capture process at waiting-point nucleus 64Ge, Nature Physics (2023). DOI: 10.1038/s41567-023-02034-2

Journal information: Nature Physics 

Provided by Chinese Academy of Sciences 

A broad systematic review has revealed that quantum computing applications in health care remain more theoretical than practical, despite growing excitement in the field.

The comprehensive study published in npj Digital Medicine, which analyzed 4,915 research papers published between 2015 and 2024, found little evidence that quantum machine learning (QML) algorithms currently offer any meaningful advantage over classical computing methods for health care applications.

“Despite exponential growth in research claiming quantum benefits for health care, our analysis shows no consistent evidence that quantum algorithms outperform classical methods for clinical decision-making or health service delivery,” said Dr. Riddhi Gupta from the School of Mathematics and Physics and the Queensland Digital Health Center (QDHeC) at the University of Queensland.

The review identified several critical gaps in current research approaches:

• Only 16 of 169 eligible studies actually tested their algorithms under realistic quantum hardware conditions, with most relying solely on idealized simulations
• Most research failed to address critical factors like noise characterization, error mitigation, or performance scaling as problem size increases
• Applications were narrowly focused on clinical diagnosis and prediction, with minimal exploration of health service delivery or public health applications
• Data encoding scalability remains problematic, often requiring hardware assumptions that don’t exist in current quantum systems

Dr. Gupta said that while quantum computing holds tremendous theoretical promise for health care, this review provides an important reality check on the current state of the technology.

“The field needs to address these methodological challenges before quantum methods can deliver meaningful advantages in health data processing,” she said.

The researchers propose new standards for evaluating quantum computing applications in health care, including minimum requirements for demonstrating scalability and performance under realistic conditions.

QDHeC’s Deputy Director, Professor Jason Pole, said that this study confirms that while quantum technology is promising, it is not going to change health care next week.

“Decision makers get understandably excited when we talk about the possibilities of quantum computing in health care, but Dr. Gupta’s study affirms that we still have a lot of work to do before we can apply this technology in a useful and strategic way.”

Senior author of the study, Associate Professor Sally Shrapnel who leads the QDHeC Quantum Program and is Deputy Director of the Australian Research Council’s Center of Excellence for Engineered Quantum Systems (EQUS) says that despite these challenges, researchers are optimistic about the future of quantum computing in health care.

“This review captures the current state of play, but the field is advancing rapidly with impressive progress from both universities and companies,” she said.

“I have no doubt we will see exciting quantum applications in digital health care in the future.”

In recent years, many physicists and material scientists have been studying superconductors, materials that can conduct direct current electricity without energy loss when cooled under a particular temperature. These materials could have numerous valuable applications, for instance generating energy for imaging machines (e.g., MRI scanners), trains, and other technological systems.

Researchers at Fudan University, Shanghai Qi Zhi Institute, Hong Kong University of Science and Technology, and other institutes in China have recently uncovered a new mechanism to generate anisotropically-enhanced in-plane upper critical field in atomically thin centrosymmetric superconductors with topological band inversions. Their paper, published in Nature Physics, specifically demonstrated this mechanism on a thin layer of 2M-WS₂, a material that has recently attracted much research attention.

“In 2020, a paper by our theoretical collaborator Prof. K.T. Law proposed that 2D centrosymmetric superconductors with a topological band inversion, such as 1T′-WTe₂ exhibit a distinct type of superconductivity, called spin-orbit-parity coupled (SOPC) superconductivity,” Enze Zhang, one of the researchers who carried out the study, told Phys.org.

“SOPC is predicted to produce novel superconductivity near the topological band crossing with both largely enhanced and anisotropic spin susceptibility with respect to in-plane magnetic field directions. At that time, we were conducting research on the superconducting properties of atomically thin 2M-WS₂, so after talking with Prof. K.T. Law, we felt that the emergent van der Waals superconductor 2M-WS₂ would most likely be a promising candidate for spin-orbit-parity coupled superconductivity.”

The structure of monolayer 2M-WS₂ is identical to that of 1T′-WTe₂, the material previously investigated by Prof. Law and his team. 2M-WS₂, however, has a unique stacking mode, which distinguishes it from other transition metal dichalcogenides.

The researchers previously found that in its bulk form, this material exhibit a high superconducting transition temperature T_C of 8.8 K. In addition, theoretical calculations suggested that atomically thin layers of 2M-WS₂ hold topological edge states with band inversion.

In their experiments, Zhang and his colleagues measured the in-plane upper critical field at a high magnetic field and confirmed the violation of the Pauli limit law. They also observed a strongly anisotropic two-fold symmetry in the material, in response to the in-plane magnetic field direction.

“Tunneling experiments conducted under high in-plane magnetic fields also showed that the superconducting gap in atomically thin 2M-WS₂ possesses an anisotropic magnetic response along different in-plane magnetic field directions, and it persists much above the Pauli limit,” Zhang explained. “Using self-consistent mean-field calculations, our theoretical collaborators conclude that these unusual behaviors originate from the strong spin-orbit-parity coupling arising from the topological band inversion in 2M-WS₂.”

The researchers’ experiments spanned across several steps. Firstly, the team performed magneto-transport measurements on atomically thin 2M-WS₂ and found that its in-plane upper critical field is not only far beyond the Pauli paramagnetic limit, but also exhibits a strongly anisotropic two-fold symmetry in response to the in-plane magnetic field direction.

Subsequently, they used tunneling spectroscopy to collect measurements under high in-plane magnetic fields. These measurements revealed that the superconducting gap in atomically thin 2M-WS₂ possesses an anisotropic magnetic response along different in-plane magnetic field directions, which persists much above the Pauli limit.

Finally, the researchers performed a series of self-consistent mean-field calculations to better understand the origin of the unusual behaviors they observed in their sample. Based on their results, they concluded that these behaviors originate from the strong spin-orbit-parity coupling arising from the topological band inversion in 2M-WS₂, which effectively pins the spin of states near the topological band crossing and renormalizes the effect of external Zeeman fields anisotropically.

“We uncovered a new mechanism for generating an anisotropically-enhanced in-plane upper critical field in atomically thin centrosymmetric superconductors with topological band inversions, highlighting 2D 2M-WS₂ as a wonderful platform for the study of exotic superconducting phenomena such as higher-order topological superconductivity and further device applications,” Zhang said.

“The novel properties found here are highly nontrivial as they directly reflect a strong SOPC inheriting from the topological band inversion in the normal state of 2M-WS₂, which had been ignored for many years in previous studies of centrosymmetric superconductors.”

In recent years, more research teams worldwide have been exploring the properties and mechanisms of centrosymmetric superconducting transition metal dichalcogenides (TMDs), such as monolayer superconducting 1T′-MoS₂, and 1T′-WTe₂, due to the characteristic co-existence of topological band structure and superconductivity within them.

The recent paper by Zhang and his colleagues could pave the way towards the exploration of large enhanced and strongly anisotropic in-plane upper critical fields, which could further improve the current understanding of these materials’ exotic physics.

“We now plan to explore the usual superconducting properties (such as the in-plane upper critical field and tunneling spectroscopy behavior at high magnetic field) of more atomically thin centrosymmetric superconductors with topological band inversions,” Zhang added.

More information: Enze Zhang et al, Spin–orbit–parity coupled superconductivity in atomically thin 2M-WS2, Nature Physics (2022). DOI: 10.1038/s41567-022-01812-8

Ying-Ming Xie et al, Spin-Orbit-Parity-Coupled Superconductivity in Topological Monolayer WTe2, Physical Review Letters (2020). DOI: 10.1103/PhysRevLett.125.107001

Journal information: Physical Review Letters  , Nature Physics 

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