Category: Physics

Colloidal gels are complex systems made up of microscopic particles dispersed in a liquid, ultimately producing a semi-solid network. These materials have unique and advantageous properties that can be tuned using external forces, which have been the focus of various physics studies.

Researchers at University of Copenhagen in Denmark and the UGC-DAE Consortium for Scientific Research in India recently ran simulations and performed analyses aimed at understanding how the injection of active particles, such as swimming bacteria, would influence colloidal gels.

Their paper, published in Physical Review Letters, shows that active particles can influence the structure of 3D colloidal gels, kneading them into porous and denser structures.

“Traditionally, much of physics focuses on systems that evolve toward their most stable or ‘favorable’ state, referred to as equilibrium,” Kristian Thijssen, senior author of the paper, told Phys.org.

“For instance, a gas or liquid that spreads evenly to fill its container is considered to be in equilibrium. However, in the physical world we inhabit, many systems do not reach equilibrium within the timescales of practical interest, or they remain continually energized in some way.”

An example of systems that remain continually energized to some extent is glass. The arrangement of particles is known to prevent the material from relaxing into its most thermodynamically stable state, which translates into a high sensitivity to its formation history.

“This is evident in glassblowing, where the process of shaping the material directly influences its internal structure,” explained Thijssen. “Colloidal gels, which consist of networks of particles with large voids, exhibit similar behavior. Their structure is not only influenced by their initial formation but also by the forces exerted on them.”

An emerging research field, known as active matter, has been trying to understand how living systems behave as far-from-equilibrium systems. This entails studying the behavior of living organisms, such as bacteria, when they are introduced into various environments.

These organisms introduce energy into their surroundings, by moving or swimming with the energy they acquire from food or other energy sources. This injection of energy prevents a system from reaching a state of equilibrium, continuously influencing their behavior.

“In our research, we sought to investigate what occurs when these two systems combine,” said Thijssen. “Specifically, we explored the dynamics of a gel, which is normally dependent on its history, when subjected to active particles that locally inject energy into their surroundings.”

Thijssen and his colleagues initially predicted that active particles would simply compress a gel into a more compact state, as this is what was observed in two-dimensional (2D) systems. Surprisingly, however, they found that their effect on 3D colloidal gels was far more intriguing.

“Instead of merely compacting the gel, the active particles reorganized the gel into a denser structure while preserving sufficient pathways for particle movement,” said Thijssen. “In this way, the gel is adapted to facilitate the transport of the active particles, resulting in a dynamic and efficient structure that continuously evolves as the active particles interact with it.”

To investigate the effects of injected active particles on 3D gels, the researchers ran a series of computer simulations using the open-source platform LAMMPS, which modeled the dynamics of gel particles and active particles. To simulate the gel particles, they used a model known as “short-range sticky potential” that captures the formation of colloidal gels.

“When colloidal particles are mixed with smaller particles in a liquid, the polymers around the colloids tend to spread evenly throughout the fluid,” said Thijssen.

“However, when two colloidal particles approach each other closely, the polymers can no longer fit between them, leading to a repulsive force that pushes the particles together. This results in attractive forces strong enough to drive the formation of a gel structure.”

To simulate the active particles, the team drew inspiration from a model describing the behavior of swimming bacteria called active Brownian particles (ABPs). These particles are known to self-propel in one direction, which they periodically change, mimicking the ‘run-and-tumble’ motion of bacteria.

“To understand how the gel responds to these active particles, we applied a technique called topological data analysis (TDA),” explained Thijssen.

“Although TDA has been used in other fields, it has not been widely applied to gels or active matter systems. TDA allows us to analyze the gel’s structure based on its topology, or overall shape. For example, a sphere would be classified as a single connected component, a ring would have one hole, and a shell would have a cavity in the center.”

Using this technique, the researchers characterized the structure of the colloidal gel in ways that unveiled crucial mechanical properties. They particularly focused on the connections between the empty spaces within a gel, which active particles use to move through the material.

“This connectivity is crucial because the active particles can alter the gel’s structure, creating more accessible pathways for movement,” said Thijssen.

The simulations and analyses carried out by the researchers yielded very interesting results. Firstly, they revealed that when injected with active particles, 3D colloidal gels restructure themselves into more compact and energetically favorable structures, while retaining several spaces that the particles can traverse.

This adaptation was only identifiable using TDA, thus demonstrating the potential of this analytical tool. In this case, TDA allowed the researchers to unveil the dynamic adaptation of colloidal gels in response to the movement of active particles.

“Our study demonstrates how Topological Data Analysis (TDA) can be leveraged to quantify gel structures,” said Thijssen. “This innovative approach offers new insights into the mechanical properties of gels and other porous materials, which have long posed challenges to comprehensive understanding.”

This recent work also demonstrates that there is a fundamental topological difference between 2D and 3D systems in adaptable materials. In 2D materials, empty regions can only form enclosed spaces that trap any particles within them.

In 3D systems, on the other hand, empty regions form both enclosed and interconnected spaces, which allow particles to move freely through networks of spaces.

“This distinction has profound implications for understanding the behavior of porous media—beyond just gels—in response to reconfigurations driven by living organisms,” said Thijssen.

“By bridging this gap, our work paves the way for more accurate models and predictions of how a diverse range of materials—ranging from biological tissues to engineered systems—respond to dynamic changes in their environments.”

This study could soon pave the way for further investigations focusing on the impact of active particles on both colloidal gels and other porous materials. In their next studies, the team plan to build on their findings to carry out additional simulations and analysis that integrate models of other materials or more complex living organisms.

“In this project, we used relatively simple active particles as models for living organisms,” said Thijssen. “However, in densely packed living systems—such as swarming bacteria or flocks of birds—collective motion often emerges from the interactions between individual agents. This motion is a defining characteristic of active systems, but it is also strongly influenced by the surrounding environment.”

A further interesting aspect of the evolution of porous media observed by the researchers is that it could also produce feedback loops. In other words, the motion of the active particles could adjust in response to the evolving porous structures, which could produce dynamic interactions with even more complex outcomes.

“Exploring these feedback mechanisms is a promising direction for future research,” added Thijssen.

“Understanding these dynamics could have practical applications in areas such as regulating bacterial movement to enhance biodegradation, preventing contamination in industrial piping systems, or managing bacterial infections by disrupting their ability to penetrate mucosal membranes.”

More information: Martin Cramer Pedersen et al, Active Particles Knead Three-Dimensional Gels into Porous Structures, Physical Review Letters (2024). DOI: 10.1103/PhysRevLett.133.228301. On arXiv: arxiv.org/html/2404.07767v1

Journal information: Physical Review Letters  , arXiv 

Northwestern University engineers are the first to successfully demonstrate quantum teleportation over a fiberoptic cable already carrying internet traffic.

The discovery introduces the new possibility of combining quantum communication with existing internet cables—greatly simplifying the infrastructure required for distributed quantum sensing or computing applications.

The study is published on the arXiv preprint server and is due to appear in the journal Optica.

“This is incredibly exciting because nobody thought it was possible,” said Northwestern’s Prem Kumar, who led the study. “Our work shows a path towards next-generation quantum and classical networks sharing a unified fiberoptic infrastructure. Basically, it opens the door to pushing quantum communications to the next level.”

An expert in quantum communication, Kumar is a professor of electrical and computer engineering at Northwestern’s McCormick School of Engineering, where he directs the Center for Photonic Communication and Computing.

Only limited by the speed of light, quantum teleportation could make communications nearly instantaneous. The process works by harnessing quantum entanglement, a technique in which two particles are linked, regardless of the distance between them. Instead of particles physically traveling to deliver information, entangled particles exchange information over great distances—without physically carrying it.

“In optical communications, all signals are converted to light,” Kumar explained. “While conventional signals for classical communications typically comprise millions of particles of light, quantum information uses single photons.”

Before Kumar’s new study, conventional wisdom suggested that individual photons would drown in cables filled with the millions of light particles carrying classical communications. It would be like a flimsy bicycle trying to navigate through a crowded tunnel of speeding heavy-duty trucks.

Kumar and his team, however, found a way to help the delicate photons steer clear of the busy traffic. After conducting in-depth studies of how light scatters within fiberoptic cables, the researchers found a less crowded wavelength of light to place their photons. Then, they added special filters to reduce noise from regular internet traffic.

“We carefully studied how light is scattered and placed our photons at a judicial point where that scattering mechanism is minimized,” Kumar said. “We found we could perform quantum communication without interference from the classical channels that are simultaneously present.”

To test the new method, Kumar and his team set up a 30 kilometer-long fiberoptic cable with a photon at either end. Then, they simultaneously sent quantum information and regular internet traffic through it. Finally, they measured the quality of the quantum information at the receiving end while executing the teleportation protocol by making quantum measurements at the mid-point. The researchers found the quantum information was successfully transmitted—even with busy internet traffic whizzing by.

Next, Kumar plans to extend the experiments over longer distances. He also plans to use two pairs of entangled photons—rather than one pair—to demonstrate entanglement swapping, another important milestone leading to distributed quantum applications. Finally, his team is exploring the possibility of carrying out experiments over real-world inground optical cables rather than on spools in the lab. But, even with more work to do, Kumar is optimistic.

“Quantum teleportation has the ability to provide quantum connectivity securely between geographically distant nodes,” Kumar said. “But many people have long assumed that nobody would build specialized infrastructure to send particles of light. If we choose the wavelengths properly, we won’t have to build new infrastructure. Classical communications and quantum communications can coexist.”

More information: Quantum teleportation coexisting with classical communications in optical fiber, Optica (2024).

Preprint: Jordan M. Thomas et al, Quantum teleportation coexisting with classical communications in optical fiber, arXiv (2024). DOI: 10.48550/arxiv.2404.10738

Journal information: Optica  , arXiv 

Provided by Northwestern University 

Quantum computing offers the potential to solve complex problems faster than classical computers by leveraging the principles of quantum mechanics. Significant advancements have been made in areas, such as artificial intelligence, cryptography, deep learning, optimization, and solving complex equations.

While major technology companies like IBM, Google, and Microsoft are working toward practical quantum computers capable of handling larger quantum information, significant challenges remain before quantum technology can be widely adopted.

Although quantum communication and cryptography are increasingly used in commercial applications owing to their secure systems, quantum communication and cryptography must undergo rigorous verification for use in security-critical applications. These processes are essential to ensure no lapses in safety or security.

To address this gap, Assistant Professor Canh Minh Do, along with Associate Professor Tsubasa Takagi and Professor Kazuhiro Ogata from the Japan Advanced Institute of Science and Technology (JAIST), Japan, developed an automated approach to verify quantum programs based on Basic Dynamic Quantum Logic (BDQL).

BDQL faithfully captures quantum evolution and measurement in quantum mechanics, providing a logical framework to formalize and verify quantum protocols with their desired properties. Despite its effectiveness, BDQL had limitations, particularly its inability to handle interactions between participants in quantum protocols.

To overcome these limitations, the team has now developed a new logic known as Concurrent Dynamic Quantum Logic (CDQL), which extends BDQL’s capabilities to handle concurrency in quantum protocols.

In their study published on Dec. 12 in ACM Transactions on Software Engineering and Methodology, Dr. Do explains, “CDQL effectively formalizes concurrent behaviors and communication between participants in quantum protocols.

“Our logical framework also provides a transformation from CDQL models to BDQL models, ensuring compatibility with BDQL semantics, and introduces a lazy rewriting strategy for fast verification.”

This advancement not only enhances the expressiveness of the logic but also speeds up the verification process, making it applicable to a wider range of verified practical quantum applications.

One of the major advantages of CDQL over BDQL is its ability to handle concurrent actions. While BDQL was limited to sequential actions, CDQL can model quantum protocols that require multiple actions to occur concurrently, making it better suited for real-world problems.

Additionally, the framework provides a lazy rewriting strategy to improve the efficiency of the verification process. Concretely, this strategy eliminates irrelevant interleavings from earlier stages and reuses results to avoid needless computations.

This enhances the speed and scalability of verifying quantum protocols. Despite its advantages, our framework has some limitations, such as its inability to handle quantum data sharing over quantum channels. However, Dr. Do and his team plan to resolve this constraint in the future to increase CDQL’s versatility.

To improve the modeling and verification of quantum protocols, the CDQL has been developed as an extension of BDQL. The research team has successfully formalized and verified various quantum communication protocols in both BDQL and CDQL.

“Our automated formal verification approach, using both BDQL and CDQL, provides a rigorous framework for verifying both sequential and concurrent models of quantum protocols. This contributes to the reliability of foundational technologies such as quantum communication, quantum cryptography, and distributed quantum computing systems,” explains Dr. Do.

This work highlights the importance of ensuring the correctness of quantum protocols before they are deployed in critical applications.

In conclusion, CDQL is more effective than BDQL for formalizing quantum protocols with concurrent actions.

“This work introduces an automated approach using CDQL to verify the correctness of quantum protocols, ensuring their reliability before deployment in safety-critical and security-critical applications,” concludes Dr. Do.

He further adds, “By ensuring the correctness of quantum protocols, this work contributes to the development of reliable, bug-free quantum technologies, particularly in quantum communication and cryptography, over the next five to 10 years.”

This study represents a significant advancement in the formal verification of quantum protocols, contributing to the reliability, security, and practical applicability of quantum technologies.

More information: Canh Minh Do et al, Automated Quantum Protocol Verification Based on Concurrent Dynamic Quantum Logic, ACM Transactions on Software Engineering and Methodology (2024). DOI: 10.1145/3708475

Provided by Japan Advanced Institute of Science and Technology 

Neither gas nor liquid, supercritical fluids exhibit a unique mashup of the properties of both and arise when fluids are pushed to very high temperatures and pressures. Their properties make them ideal for a wide variety of chemical, pharmaceutical and environmental applications.

Supercritical carbon dioxide, for example, is often used to decaffeinate coffee—its liquid-like high density and gas-like rapid diffusion allows it to easily penetrate coffee beans and selectively extract the caffeine while preserving the beloved coffee taste.

In carbon capture and sequestration, carbon dioxide emissions are stored underground in their supercritical fluid form to combat climate change. It’s also found in rocket propulsion systems, because it can efficiently store a lot of energy, and the atmospheres of some planets, such as Venus. It could also be used as a more environmentally friendly fluid in future cooling systems.

Now, researchers at the Department of Energy’s SLAC National Accelerator Laboratory have uncovered new details of how supercritical fluids’ special properties arise from their molecular level dynamics. Their results are published in two studies in the journals Nature Communications and Physical Review Letters.

From static studies, researchers know that the molecular structure of supercritical fluids is made up of clusters of molecules of different sizes, but they haven’t been able to study the movement of these nanosized blobs until now.

“Probing these transient, fast-moving, nanoscale clusters is a challenge,” said Matthias Ihme, a professor of photon science at SLAC National Accelerator Laboratory, a professor of mechanical engineering at Stanford and a member of the Stanford PULSE Institute. The fact that supercritical fluids only form under high pressure and temperature further complicates their study, he said.

However, recent advances in X-ray free electron lasers allowed Ihme and his colleagues to use SLAC’s Linac Coherent Light Source (LCLS) to directly observe the ultrafast dynamics of molecular clusters in supercritical carbon dioxide. Those advances, said SLAC staff scientist Yanwen Sun, involved a decade-long effort to generate two bright, nearly identical LCLS X-ray flashes in rapid succession—making it possible to capture the kinds of dynamics Ihme and his team were interested in.

By measuring how the LCLS’s X-rays scattered off the samples over time, the authors found that the dynamics of these systems evolve within picoseconds, or trillionths of a second. Specifically, these results, published in Nature Communications, showed that the blobs transition from ballistic motion, which is relatively straight and predictable, to the more random and unpredictable Brownian motion.

However, Ihme said, “the existing theory does not capture these nanometer-length, picosecond-timescale dynamics,” so the team carried out follow-up molecular dynamics simulations. The simulations revealed that the observed transition in molecular dynamics is due to collisions between unbound, isolated molecules of the substance with its nanosized clusters.

“You can think of it like a molecular pinball machine, or billiards,” Ihme said. These collisions exchange momentum between the clusters, affecting the properties of the supercritical fluid such as heat capacity, density, and viscosity, which are directly related to how the fluid reacts and mixes, among other behaviors.

“Our measurements indicate that there are significant gaps in accurately predicting properties in these complex environments,” Ihme said.

Equipped with this novel insight, the team developed a theoretical model, published in Physical Review Letters, that connects these microscopic cluster dynamics with the macroscopic properties of supercritical fluids, potentially allowing researchers to predict and tailor them.

“This model is a tool that will allow us to better understand supercritical fluids, to better predict them, and ultimately to control them,” Ihme said. “That’s what an engineer or chemist needs for practical designs.”

In this work, the team focused solely on supercritical fluid carbon dioxide. Next, they hope to investigate the dynamics of supercritical water and the manipulation of chemical reactions in supercritical fluids, which could be used to break down harmful “forever chemicals” into harmless compounds or as environmentally benign solvents for green chemistry and catalytic applications.

More information: Arijit Majumdar et al, Direct observation of ultrafast cluster dynamics in supercritical carbon dioxide using X-ray Photon Correlation Spectroscopy, Nature Communications (2024). DOI: 10.1038/s41467-024-54782-1

Jingcun Fan et al, Heterogeneous Cluster Energetics and Nonlinear Thermodynamic Response in Supercritical Fluids, Physical Review Letters (2024). DOI: 10.1103/PhysRevLett.133.248001

Journal information: Physical Review Letters  , Nature Communications 

Provided by SLAC National Accelerator Laboratory 

Quantum walks are a powerful theoretical model using quantum effects such as superposition, interference and entanglement to achieve computing power beyond classical methods.

A research team at the National Innovation Institute of Defense Technology from the Academy of Military Sciences (China) recently published a review article that thoroughly summarizes the theories and characteristics, physical implementations, applications and challenges of quantum walks and quantum walk computing. The review was published Nov. 13 in Intelligent Computing in an article titled “Quantum Walk Computing: Theory, Implementation, and Application.”

As quantum mechanical equivalents of classical random walks, quantum walks use quantum phenomena to design advanced algorithms for applications such as database search, network analysis and navigation, and quantum simulations. Different types of quantum walks include discrete-time quantum walks, continuous-time quantum walks, discontinuous quantum walks, and nonunitary quantum walks. Each model presents unique features and computational advantages.

Discrete-time quantum walks involve step-by-step transitions without a time factor, using coin-based models like Hadamard and Grover walks or coinless models such as Szegedy and staggered quantum walks for graph-based movement. In contrast, continuous-time quantum walks operate on graphs using time-independent Hamiltonians, making them particularly useful for spatial searches and traversal problems.

Discontinuous quantum walks combine the properties of both discrete-time and continuous-time models, enabling universal computation through perfect state transfers. Meanwhile, nonunitary quantum walks, including stochastic quantum walks and open quantum walks, act as open quantum systems and find applications in simulating photosynthesis and quantum Markov processes.

The two original branches, discrete-time and continuous-time quantum walks, achieve faster diffusion than classical random walk models and exhibit similar probability distributions. To some extent, discrete-time and continuous-time models are interchangeable. In addition, various discrete models can be interchanged based on the graph structure, highlighting the versatility of quantum walk models.

According to the authors, quantum walks not only have evolutionary merits, but also improve sampling efficiency, solving problems previously considered computationally difficult for classical systems.

The wide variety of physical quantum systems used to implement quantum walks demonstrates the utility of discrete-time and continuous-time quantum walk models and quantum-walk-based algorithms. There are two different approaches to physically implementing quantum walks:

• Analog physical simulation primarily uses solid-state, optical and photonic systems to directly implement specific Hamiltonians without translation into quantum logic. This approach enables scalability by increasing particle numbers and dimensions but lacks error correction and fault tolerance. It faces challenges in efficiently simulating large graphs.
• Digital physical simulation constructs quantum circuits to simulate quantum walks, offering error correction and fault tolerance. Designing efficient circuits remains difficult, but digital implementations can achieve quantum speedup and simulate a variety of graphs.

Quantum walk applications are categorized into four main categories: quantum computing, quantum simulation, quantum information processing and graph-theoretic applications.

• Quantum Computing: Quantum walks enable universal quantum computation and accelerate computations in algebraic and number-theoretic problems. They are also being explored for applications in machine learning and optimization.
• Quantum Simulation: Quantum walks are an important tool for simulating the behavior of uncontrollable quantum systems, providing insight into complex quantum phenomena that are difficult or impossible to analyze classically. Applications include simulating multi-particle systems, solving complex physics problems, and modeling biochemical processes.
• Quantum Information Processing: Quantum walks are used for the preparation, manipulation, characterization and transmission of quantum states, as well as in quantum cryptography and security applications.
• Graph-Theoretic Applications: Quantum walks, associated with graph structures, provide promising solutions for graph-theoretic problems and various network applications. They are used to explore graph characteristics, rank vertex centrality and identify structural differences between graphs.

Despite rapid progress, practical quantum walk computing faces challenges, including devising effective algorithms, scaling up the physical implementations and implementing quantum walks with error correction or fault tolerance. These challenges, however, provide a roadmap for future innovations and advancements in the field.

More information: Xiaogang Qiang et al, Quantum Walk Computing: Theory, Implementation, and Application, Intelligent Computing (2024). DOI: 10.34133/icomputing.0097

Provided by Intelligent Computing 

Researchers at the Fritz Haber Institute have developed the Automatic Process Explorer (APE), an approach that enhances our understanding of atomic and molecular processes. By dynamically refining simulations, APE has uncovered unexpected complexities in the oxidation of palladium (Pd) surfaces, offering new insights into catalyst behavior. The study is published in the journal Physical Review Letters.

Kinetic Monte Carlo (kMC) simulations are essential for studying the long-term evolution of atomic and molecular processes. They are widely used in fields like surface catalysis, where reactions on material surfaces are crucial for developing efficient catalysts that accelerate reactions in energy production and pollution control. Traditional kMC simulations rely on predefined inputs, which can limit their ability to capture complex atomic movements. This is where the Automatic Process Explorer (APE) comes in.

Developed by the Theory Department at the Fritz Haber Institute, APE overcomes biases in traditional kMC simulations by dynamically updating the list of processes based on the system’s current state. This approach encourages exploration of new structures, promoting diversity and efficiency in structural exploration. APE separates process exploration from kMC simulations, using fuzzy machine-learning classification to identify distinct atomic environments. This allows for a broader exploration of potential atomic movements.

By integrating APE with machine-learned interatomic potentials (MLIPs), researchers applied it to the early-stage oxidation of palladium surfaces, a key system in pollution control. When applied to the early-stage oxidation of a palladium surface, a key material used in catalytic converters for cars to reduce emissions, APE uncovered nearly 3,000 processes, far exceeding the capabilities of traditional kMC simulations. These findings reveal complex atomic motions and restructuring processes that occur on timescales similar to molecular processes in catalysis.

The APE methodology provides a detailed understanding of Pd surface restructuring during oxidation, revealing complexities previously unseen. This research enhances our knowledge of nanostructure evolution and its role in surface catalysis. By improving the efficiency of catalysts, these insights have the potential to significantly impact energy production and environmental protection, contributing to cleaner technologies and more sustainable industrial processes.

More information: King Chun Lai et al, Automatic Process Exploration through Machine Learning Assisted Transition State Searches, Physical Review Letters (2025). DOI: 10.1103/PhysRevLett.134.096201

Journal information: Physical Review Letters 

Provided by Max Planck Society 

In a new Physical Review Letters study, researchers propose an experimental approach that could finally determine whether gravity is fundamentally classical or quantum in nature.

The nature of gravity has puzzled physicists for decades. Gravity is one of the four fundamental forces, but it has resisted integration into the quantum framework, unlike the electromagnetic, strong, and weak nuclear forces.

Rather than directly tackling the challenging problem of constructing a complete quantum theory of gravity or trying to detect individual gravitons—the hypothetical mediator of gravity—the researchers take a different approach.

Phys.org spoke to the researchers behind the study to gain insight into their unique approach.

“Several proposals have appeared in the past years that, in principle, allow us to determine gravity’s nature experimentally, but their experimental requirements are extraordinarily challenging. So our motivation was to come up with a more feasible experiment that would have the power to at least falsify that gravity is classical,” explained Serhii Kryhin, a third-year graduate student at Harvard University and a co-author of the study.

The researchers aimed to rephrase the age-old question into one that could provide more concrete results: “What measurable differences would tell us whether gravity needs to be quantized?”

Quantum vs. classical fluctuations

“The idea is very simple yet remained unnoticed all this time. If gravity is quantum, as a long-range force, it should be able to induce quantum entanglement of distant matter. However, if gravity is fundamentally classical, no entanglement can be produced,” said Vivishek Sudhir, Associate Professor at MIT and co-author of the study.

The insight is that if gravity is classical, it must exhibit irreducible stochastic fluctuations. These fluctuations are a necessity, stemming from a fundamental inconsistency that would arise without them—the deterministic nature of gravity (due to being classical) would violate the principles of quantum mechanics.

The brilliance comes in recognizing that these fluctuations would leave behind a signature in the cross-correlation spectrum as a phase shift, differing from what would be produced if gravity was quantum.

“Quantum fluctuations always arise as quantum fluctuations of dynamic degrees of freedom of general relativity. From a practical perspective, the main difference between quantum and classical gravity fluctuations comes in the magnitude. Being relativistic effects, quantum fluctuations are notoriously weak and thus incredibly challenging to measure,” said Kryhin.

“On the other hand, classical fluctuations, if they exist and have to remain consistent with everything else we know, appear to be much larger,” added Prof. Sudhir.

Mathematical framework

The researchers propose a theoretical framework for this quantum-classical interaction in the Newtonian limit of gravity. In this framework, classical gravity and quantum matter co-exist.

They created a quantum-classical master equation describing how quantum matter and classical gravity evolve together. They also derived a Hamiltonian for Newtonian gravity’s interaction with quantum masses through two complementary approaches—Dirac’s theory of constrained systems and the Newtonian limit of gravity.

Next, they formulated a modified quantum Newton’s law that accounts for stochastic gravitational effects and finally calculated the distinctive correlation patterns between two quantum oscillators interacting gravitationally.

This mathematical framework led them to a closed Lindblad equation (Markovian master equation) for quantum matter interacting with classical gravity. This equation includes a term proportional to the parameter ε, which distinguishes between classical gravity (ε ≠ 0) and quantum gravity (ε = 0).

Identifying measurable quantities

The researchers derived several crucial results. They showed that, contrary to previous claims, a consistent theory of classical gravity interacting with quantum matter is indeed possible.

Their calculations reveal that classical gravity would induce fluctuations distinct from its quantum counterpart. Crucially, they identify an experimentally measurable signature.

When two quantum harmonic oscillators interact gravitationally, their cross-correlation spectrum shows a characteristic phase shift of π or 180 degrees at a specific detuning from resonance if gravity is classical.

To test these predictions, the researchers propose what amounts to a quantum version of the historic Cavendish experiment, using two highly coherent quantum mechanical oscillators coupled gravitationally.

The researchers could observe the characteristic phase shift by precisely measuring the cross-correlation of their motions.

What distinguishes this approach from previous proposals is its experimental feasibility. Unlike other tests that might require creating massive objects in quantum superposition states, this experiment relies on correlations between quantum oscillators within the reach of current or near-future technology.

Prof. Sudhir noted, “Semiclassical models of gravity usually explicitly neglect the backaction of quantum fluctuations of matter onto the classical gravity dynamics. In contrast, our theory allows self-consistent dynamics of classical gravity field and quantum matter.”

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Jury’s still out

An experimental confirmation that gravity is classical would have profound implications for our physical theories.

“At present, it is taken as a self-evident fact that gravity has to be quantum, although nobody precisely knows what that means!” said Kryhin.

“Immense effort has been made to understand the behavior of quantized general relativity and construct a complete theory of quantum gravity, which resulted in the construction of string theory as one of the byproducts. If experimentally proven that gravity is classical, we will have to start from the beginning in a search for a satisfactory ontological picture of the world.”

While the study offers a fresh perspective on a question that has plagued physicists for decades, they acknowledge the many problems to be addressed, from formalism development and model-building to demonstrating the technologies required for the experiment.

“From an experimental standpoint, we need two gravitating masses, noise isolation, and measurement techniques, all of which need to come together to realize the sensitivity needed for a decisive experiment,” concluded Kryhin.

More information: Serhii Kryhin et al, Distinguishable Consequence of Classical Gravity on Quantum Matter, Physical Review Letters (2025). DOI: 10.1103/PhysRevLett.134.061501. On arXiv: DOI: 10.48550/arxiv.2309.09105

Journal information: Physical Review Letters  , arXiv 

© 2025 Science X Network

Neutrinos generated through solar fusion reactions travel effortlessly through the sun’s dense core. Each specific fusion process creates neutrinos with distinctive signatures, potentially providing a method to examine the sun’s internal structure. Multiple neutrino detection observatories on Earth are now capturing these solar particles, which can be analyzed alongside reactor-produced neutrinos with the data eventually enabling researchers to construct a detailed map of the interior of the sun.

The sun is a massive sphere of hot plasma at the center of our solar system and provides the light and heat to make life on Earth possible. Composed mostly of hydrogen and helium, it generates energy through nuclear fusion, converting hydrogen into helium in its core. This process releases an enormous amount of energy which we perceive as heat and light.

The sun’s surface, or photosphere, is around 5,500°C, while its core reaches over 15 million°C. It influences everything from our climate to space weather, sending out solar wind and occasional bursts of radiation known as solar flares. As an average middle-aged star, the sun is about 4.6 billion years old and will (hopefully) continue burning for another 5 billion years before evolving into a red giant and eventually becoming a white dwarf.

The standard solar model (SSM) is used to understand and predict the sun’s internal structure and evolution. It’s how we work out what’s going on inside the sun. It explains how, in the sun’s core, different nuclear fusion reactions are constantly pumping out neutrinos—tiny, nearly massless particles that travel through almost anything.

Each type of reaction creates neutrinos with their own properties. These neutrinos may help us to understand more about the interior of the sun. Right now, we only know about its internal density structure from theoretical models based on the SSM, matched with what we can see on the sun’s surface. The neutrinos may hold information that will give us more direct data about the solar interior.

Chinese researchers are working on a new neutrino observatory called TRIDENT. They built an underwater simulator to develop their plan.

In a paper published by Peter B. Denton from the Brookhaven National Laboratory and Charles Gourley from Rensselaer Polytechnic Institute show how solar neutrinos can help us to look inside the sun and establish its density structure. In contrast, photons of light only tell us about the surface of the sun as it is right now, and give us little information about the sun’s interior hundreds of thousands of years ago. This delay in photons exiting the sun is because they bounce around the dense solar interior for centuries before escaping. Neutrinos, on the other hand, give us up-to-the-minute information because they can zip straight through the sun without getting stopped.

The study is published on the arXiv preprint server.

It has long since been known that neutrinos change their flavor or type (electron neutrino, muon neutrino or tau neutrino) as they travel through matter and that depends on the local density. This is well documented as the Mikheyev-Smirnov-Wolfenstein effect and, by measuring the flux of the neutrino as observed on Earth, compared to the unoscillating predicted flux, the density where the neutrinos were produced can be calculated. Input is also required from independent measurements of neutrino oscillations that have been created inside nuclear reactors.

The team demonstrated that the approach does have its limitations and that there are constraints on just how much density information can be gleaned from the SSM alone. Further data from projects like JUNO and DUNE is needed to further improve the solar internal density profile and give us a more realistic view of the internal workings of our local star.

More information: Peter B. Denton et al, Determining the Density of the Sun with Neutrinos, arXiv (2025). DOI: 10.48550/arxiv.2502.17546

Journal information: arXiv 

Provided by Universe Today 

A small international team of nanotechnologists, engineers and physicists has developed a way to force laser light into becoming a supersolid. Their paper is published in the journal Nature. The editors at Nature have published a Research Briefing in the same issue summarizing the work.

Supersolids are entities that exist only in the quantum world, and, up until now, they have all been made using atoms. Prior research has shown that they have zero viscosity and are formed in crystal-like structures similar to the way atoms are arranged in salt crystals.

Because of their nature, supersolids have been created in extremely cold environments where the quantum effects can be seen. Notably, one of the team members on this new effort was part of the team that demonstrated more than a decade ago that light could become a fluid under the right set of circumstances.

To create their supersolid, the researchers fired a laser at a piece of gallium arsenide that had been shaped with special ridges. As the light struck the ridges, interactions between it and the material resulted in the formation of polaritons—a kind of hybrid particle—which were constrained by the ridges in a predesigned way. Doing so forced the polaritons into forming themselves into a supersolid.

The research team then set themselves the task of testing it to make sure it truly was a supersolid—a task made more difficult by the fact that a supersolid made from light had never been created before. Despite the difficulties, they were able to show that their supersolid was both a solid and a fluid and that it had no viscosity.

The team plans to continue their work with the light-made supersolid to learn more about its structure. They note that supersolids made from light might be easier to work with than those made with atoms, which could help us better understand the nature of supersolids in general.

More information: Dimitrios Trypogeorgos et al, Emerging supersolidity in photonic-crystal polariton condensates, Nature (2025). DOI: 10.1038/s41586-025-08616-9

A supersolid made using photons, Nature (2025). DOI: 10.1038/d41586-025-00637-8

Journal information: Nature 

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Many physicists and engineers have recently been trying to demonstrate the potential of quantum computers for tackling some problems that are particularly demanding and are difficult to solve for classical computers. A task that has been found to be challenging for both quantum and classical computers is finding the ground state (i.e., lowest possible energy state) of systems with multiple interacting quantum particles, called quantum many-body systems.

When one of these systems is placed in a thermal bath (i.e., an environment with a fixed temperature that interacts with the systems), it is known to cool down without always reaching its ground state. In some instances, a quantum system can get trapped at a so-called local minimum; a state in which its energy is lower than other neighboring states but not at the lowest possible level.

Researchers at California Institute of Technology and the AWS Center for Quantum Computing recently showed that while finding the local minimum for a system is difficult for classical computers, it could be far easier for quantum computers.

Their paper, published in Nature Physics, introduces a new quantum algorithm that simulates natural cooling processes, which was successfully used to predict the local minima of quantum many-body systems.

“This paper emerged from a fundamental question: should quantum theorists focus solely on ground states when they’re often physically unrealizable due to the inherent computational hardness in finding them?” Hsin-Yuan (Robert) Huang, co-first author of the paper, told Phys.org.

“In machine learning, local minima—not global minima—are what practical algorithms find and use successfully. This sparked our curiosity about local minima in quantum systems.”

The recent work by Huang and his colleagues combines approaches from three different areas of physics research. These include the study of local minima and their physical relevance, the ongoing quest to demonstrate the advantages of quantum computers in optimization problems and recent insights from the field of quantum thermodynamics.

“This convergence enabled us to define quantum local minima through thermal perturbations—a physically meaningful approach that mirrors what happens when nature cools a physical system,” said Huang. “Our objective was to determine if finding local minima could provide a provable quantum advantage while maintaining direct connections to natural physical processes.”

To tackle the problem of finding a local minimum, the researchers first formalized the natural cooling process of quantum systems. Instead of seeking ground states, which are global energy minima, they focused on local minima, states in which small perturbations no longer decrease the energy of a system in a thermal bath.

“Our analysis proceeded to show that the problem of cooling to local minima is classically hard and quantumly easy,” said Leo Zhou.

“To establish classical hardness, we provide explicit construction of quantum systems where any local minima can be used to encode universal quantum computation, a task widely believed to be classically intractable.

“We then developed a quantum thermal gradient descent algorithm, which enables a quantum computer to efficiently find a local minimum by mimicking natural cooling processes.”

Comparison between thermal perturbations and local unitary perturbations. Credit: Chen et al.
The greatest technical challenge that the researchers had to overcome for this study was proving that some classically hard Hamiltonians have no suboptimal local minima, or that, in other words, their energy landscapes have a perfect bowl-like shape.

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To achieve this, they employed clever constructions from quantum complexity theory and sophisticated mathematical tools for analyzing the effects of thermal perturbations on energy landscapes.

“We found that cooling physical systems to local minima is universal for quantum computation,” said Huang.

“In other words, quantum computers can efficiently find local minima while classical computers cannot, assuming that quantum computers are more powerful than classical ones. This result is compelling because it has a clear physical interpretation: when nature cools a quantum system, it effectively solves the problem of finding local minima under thermal perturbations.”

“Furthermore, our result points to a new approach to characterize quantum many-body systems that challenges conventional wisdom,” said Zhou.

“Instead of focusing solely on ground states, we can study their local minima and overall energy landscape. Optimizing over the energy landscape can even lead to discovery of new physics—for example, by finding an anomalous local minimum with unexpected physical properties.”

The new quantum algorithms developed by Huang and his colleagues were found to formalize and replicate the natural cooling of quantum systems. Using this algorithm, the researchers showed that quantum computers could significantly enhance energy optimization, outperforming classical computers by a large margin.

“After classical algorithms reach their ‘best’ solution, our quantum algorithm could find even lower energy states—potentially transforming computational approaches in materials science, chemistry, and physics,” explained Huang.

The results attained by this team of researchers highlight the potential of quantum computing systems for finding the local minima of quantum systems. In their next studies, Huang and his colleagues plan to build on their recent work by further testing their algorithm and applying it to a broader range of scenarios.

“First, we aim to characterize physically relevant quantum systems with favorable energy landscapes where our approach could provide practical quantum advantages,” said Huang. “Second, we’re investigating whether these techniques could yield quantum advantages for classical optimization problems—potentially expanding the impact beyond quantum systems.”

As part of their next studies, the researchers are planning to carry out experimental demonstrations of their proposed method using near-term quantum devices. In addition, they will try to engineer synthetic quantum processes that could outperform the natural cooling capabilities of quantum systems.

“Our ultimate goal is not only to bridge the gap between theoretical quantum advantage and practical applications but also to pioneer new ways of understanding and controlling quantum many-body systems,” added Huang and Zhou.

More information: Chi-Fang Chen et al, Local minima in quantum systems, Nature Physics (2025). DOI: 10.1038/s41567-025-02781-4.

Journal information: Nature Physics

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