Monday, June 15, 2026

 

Newton reloaded: Dresden physicists go beyond the action–reaction principle



Technische Universität Dresden

Illustration Newton Reloaded: Dresden Physicists Go Beyond the Action–Reaction Principle 

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Flocks of birds, bacteria and tissue cells: in some collective systems, the individual elements respond to only part of their surroundings and therefore do not follow Newton’s third law, which states that action equals reaction. Physicists at the Cluster of Excellence ctd.qmat in Dresden have developed a remarkable theory that allows these exceptions to be efficiently described and simulated far more accurately. The trick is that auxiliary degrees of freedom — shown here as green birds — give the theory the flexibility it needs to precisely describe even these exceptions to Newton’s law.

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Credit: Kilian Neddermeyer





Newton and Fields of Vision

Birds have a wide field of vision. Yet when they fly in a flock, they orient themselves only toward the birds in front of them or alongside them. Because a bird never aligns itself with a bird behind it, the flock seemingly defies Newton’s third law — the principle of action and reaction, often summed up as “for every action, there is an equal and opposite reaction.” When we run, for example, our feet push against the ground and the ground pushes back with an equal but opposite force. The same principle is at work when we drive a car, jump, row, or let air escape from a balloon: when the air is expelled backward, the balloon flies forward. Everyday life is full of movements that obey Newton’s third law, which is more than 300 years old and forms a cornerstone of classical mechanics. “Whatever we normally teach our students in theoretical mechanics, it ultimately rests on the action–reaction principle,” explains research group leader Marín Bukov.

Flocks of birds, swarms of bacteria, people in crowds, and tissue cells, by contrast, do not obey Newton’s third law, because the components of these systems respond to only part of their surroundings. This makes the interaction unidirectional, meaning that “action equals reaction” no longer applies. These exceptions are known as non-reciprocal interactions. Until now, they could not be fully described with the classical theories developed for reciprocal interactions, and therefore these systems could not be simulated efficiently. Efficient simulation, however, is essential for studying processes in the human body or the motion of flocks and swarms. This research gap has now been closed by the findings of a Dresden physics team working with Roderich Moessner. Moessner is a Principal Investigator of the Würzburg–Dresden Cluster of Excellence ctd.qmat — Complexity, Topology and Dynamics in Quantum Matter — and director of the Max Planck Institute for the Physics of Complex Systems in Dresden.

Newton Reloaded: Physicists in Dresden Find an Elegant Solution

“The research team has developed and proven a theory that makes much of what we teach our students applicable to non-reciprocal systems as well. These systems, where Newton’s third law does not apply, can now finally be described exactly and simulated precisely — even using established methods. This is exactly the kind of tool that has been missing in recent years,” says Bukov.

To achieve this, the team of physicists expanded the original action–reaction framework. To describe non-reciprocal systems using the tools developed for reciprocal systems, all that is needed are additional artificial variables. Here is how it works: theoretical physicists usually model nature in equations. Each variable describes a degree of freedom that actually exists — such as the position or speed of a bird, the position of a fish in a school, or the position of a car in traffic. “The trick behind the new theory is that it constructs a partner for each component of the system — a fictitious partner that doesn’t exist in nature. The original non-reciprocal interactions are replaced by reciprocal interactions with these auxiliary degrees of freedom,” explains Bukov’s colleague Ricard Alert, a biophysicist.

What does that mean for a flock of birds? “To simulate the birds’ movements precisely, we describe the dynamic system ‘flock of birds’ using established methods — as if it were a reciprocal system, even though it is not. The elegant solution is to artificially place an fictitious bird in front of each real bird, aligned in exactly the opposite direction,” says Alert.

Putting the Results in Context, Outlook

Introducing auxiliary degrees of freedom is nothing new in physics. What is new, however, is that these auxiliary degrees of freedom now make it easier to study systems with non-reciprocal interactions. On the one hand, this allows researchers to use the established theoretical framework of many-body physics. On the other, it enables non-reciprocal systems to be simulated with much greater accuracy. Above all, the findings deepen physicists’ fundamental understanding of these processes — and such understanding is always the basis for future discoveries.

“In Würzburg and Dresden, we study quantum matter whose particles interact under certain conditions in ways that give rise to new phenomena such as magnetism or lossless current transport. The exciting question now is whether these exceptions to Newton’s law lead to entirely new forms of collective quantum behavior. We still know very little about this — and that is precisely what makes this so fascinating,” says Moessner.

The findings of the Dresden physics team have been published in the journal Nature Physics.

Publication

Hamiltonian description of non-reciprocal interactions; Yu-Bo Shi, Roderich Moessner, Ricard Alert & Marín Bukov, Nature Physics (2026), https://doi.org/10.1038/s41567-026-03317-0

ctd.qmat

The Cluster of Excellence ctd.qmat — Complexity, Topology and Dynamics in Quantum Matter — at Julius-Maximilians-Universität Würzburg and Technische Universität Dresden explores and develops novel quantum materials with tailored properties. Around 300 researchers from over 30 countries work at the interface of physics, chemistry, and materials science to lay the foundations for tomorrow’s technologies. In 2026, the cluster entered the second funding period of the German Excellence Strategy of the Federal and State Governments — with an expanded focus on the dynamics of quantum processes.

 

Game-changing solid-state 3D printing delivers ultra-tough, high-ductility aluminum components for aerospace and marine engineering




KeAi Communications Co., Ltd.
SEFSD fabrication process for 5183 aluminum alloy components. 

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SEFSD fabrication process for 5183 aluminum alloy components.

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Credit: Huihong Liu





5xxx series aluminum-magnesium alloys are highly sought after in the aerospace, automotive, and shipbuilding industries due to their low density, high strength, and excellent corrosion resistance. However, manufacturing these components using conventional melt-based 3D printing (additive manufacturing) methods is challenging; the melting and solidification processes often introduce defects such as coarse columnar grain structures, macro/micro cracks, pores, and element evaporation, which severely compromises the service performance of the printed components.

In a study published in the KeAi journal China Welding, a research team from Shanghai Jiao Tong University reported a solution: a novel solid-state 3D printing process termed screw extrusion-plasticizing friction stir deposition (SEFSD). Utilizing a specially designed three-stage tapered screw tool, the team continuously extruded and plasticized 5183 aluminum particulate feedstock via tool itself, fabricating a 20-layer deposition wall without melting the metal.

"By keeping the metal in the solid state and utilizing the intense frictional heat and severe plastic deformation of the SEFSD process, we bypass the melting phase entirely," says first author Licheng Sun. "This not only suppresses defect formation but also triggers dynamic recrystallization, yielding a homogenous, finely grained structure with exceptional strength and ductility in the deposition components."

The team's research highlighted that the printed components maintained remarkable microstructural stability despite repeated thermal cycles during the layer-by-layer deposition because of the alloy's low stacking fault energy. "In addition, since SEFSD relies on particulate feedstock, it allows for continuous feeding and easy customization of alloy compositions, overcoming the limitations of previous wire- or rod-based solid-state printing methods," adds Sun. 

Most importantly, this new method enables 'self-plasticization' without relying on a substrate constraint, it could therefore significantly reduce the thermal and mechanical forces applied onto the substrate or previously deposited layers, hence improving the processing flexibility.

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Contact the author: Huihong Liu, Shanghai Key Laboratory of Digital Manufacture for Thin-walled Structures, Shanghai Jiao Tong University, Shanghai 200240, China. liuhuihong@sjtu.edu.cn.

The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).

Self-driving cars safer and more human


New model predicts how people avoid collisions: a Delft University of Technology breakthrough


Delft University of Technology



When a leading vehicle suddenly brakes or an oncoming car unexpectedly enters your lane, you have only fractions of a second to decide whether to brake, swerve, or both. "Existing models typically describe only part of this process, such as reaction time or steering behavior," says Arkady Zgonnikov, Assistant Professor at Delft University of Technology (The Netherlands). "Our new model brings all these components together." The model integrates perception, decision-making and execution into a single coherent framework. As a result, it can detect when a situation becomes dangerous, predict how the traffic situation is likely to evolve, and simultaneously determine the most effective avoidance strategy.

To test the model’s validity, the researchers compared it with human behavior in three hazardous traffic scenarios: a leading vehicle braking suddenly, an oncoming vehicle entering the lane unexpectedly, and a car failing to yield. The model was given exactly the same information as human drivers. "The model showed realistic braking reaction times and made similar choices between braking and steering," says Zgonnikov. Moreover, it incorporates human limitations, ensuring that the resulting behavior remains recognizably human.

The researchers see important applications for both the development and evaluation of autonomous vehicles. "It can help address whether autonomous vehicles are safer than human drivers, a key question in regulation," says Zgonnikov. "At the same time, it becomes possible to formulate clear and measurable requirements for manufacturers." According to Mauricio Peña, Chief Safety Officer at Waymo, the model can help the sector to "move towards a shared, scientifically grounded approach to assessing collision avoidance."

 

Can Pepper the robot be a good playmate?


Robots can actually be good playmates, but only if they behave in ways that make sense to people.




Norwegian University of Science and Technology

Pepper the robot meets a researcher 

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Pepper and master's student Suraj De exchange information.

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Credit: Photo: Dafina Marku, NTNU






Researchers at the Norwegian University of Science and Technology (NTNU) have investigated what it is like to play a physical game with or against a robot that both looks and behaves like a person.

They conducted a controlled laboratory experiment with Pepper, a social robot designed to interact with humans.

“Our observations show that robots can actually be good playmates, but only if they behave in ways that make sense to people,” said Yavuz Inal, associate professor at NTNU’s Department of Design in Gjøvik.

So, humanoid robots can make good playmates, but their design must take into account gameplay modes, pace, role and order of play. If the robot suddenly acts like an overzealous seven-year-old who simply has to win, while also moving a bit stiffly and not quite understanding the rhythm of the game, we quickly get annoyed. We expect robots that are more natural, responsive and flexible than the current technology is capable of delivering.

When robots resemble us, we expect more

Humanoid robots such as Pepper are designed to resemble humans, in both their appearance and behaviour. They have heads, eyes, hands and facial expressions that make it easier for us to relate to them, but which can lead us to automatically expect them to behave somewhat like humans as well.

Previous research has shown that these types of characteristics increase engagement, whether the context is health, education, or pure entertainment.

Human versus machine in trash can basketball

In the study, the participants played a physical version of trash can basketball with Pepper. The human participants and Pepper the robot threw scrunched up balls of paper at a trash can from carefully chosen positions that made the game suitably challenging.

The researchers tested two gameplay modes: either humans and the robot were on the same team, or they played against each other. In addition, the order of play varied; sometimes the human participants started first, sometimes they let the robot start.

This enabled the researchers to investigate how gameplay mode and order of play affected engagement, motivation, emotional responses and enjoyment of physical activity.

“The study shows that even small adjustments in pace and order of play can be crucial in determining whether playing against a robot is perceived as fun or frustrating,” explained Inal.

The participants in the study enjoyed the game most when it was started in cooperative mode. However, there were also situations where the participants enjoyed playing against the robot. Many of the participants found competitive gameplay more exciting and motivating, especially when they were able to start the game themselves and thus felt more in control.

Beating Pepper produced a distinct sense of mastery, and some individuals admitted that it was especially satisfying when the robot missed the trash can. For these participants, competitive mode provided a clear goal and a sense of being challenged in a fun way.

Annoying when Pepper is too slow or too eager

It quickly became clear that the participants tended to get annoyed with the robot for many of the same reasons that we get annoyed with family members who are a little too competitive when playing Ludo or Monopoly.

Frustration increased especially when Pepper started the game in competition mode. The robot’s stiff movements, long pauses before each throw and slightly overzealous attempts to ‘win’ led people to expect more and become frustrated when Pepper failed to come across as either dynamic or particularly human-like. Some participants described the experience as like playing against an “overworked printer with arms”.

“When robots are invited to take on the role of playmates, we expect them to behave like proper players. If they don’t, we quickly become impatient,” asserted Inal.

The results offer a glimpse into a future where robots not only assist us at work and in the healthcare system, but also participate in everyday activities such as play, exercise and games.

Reference:
Yavuz Inal, Deepti Mishra, Suraj De: ‘The effect of cooperative and competitive human-robot interaction on player experience’ https://www.sciencedirect.com/science/article/pii/S1875952126000273


Pepper the robot 

Androgynous and 120 centimeters tall, Pepper is designed to be unintimidating in person. 

Credit

Photo: Suraj De, NTNU


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