particle motion experiments

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• Standards (40)

Next Generation Science Standards

Matter and its interactions (ms-ps1).

• Develop a model that predicts and describes changes in particle motion, temperature, and state of a pure substance when thermal energy is added or removed. (MS-PS1-4)

Energy (MS-PS3)

• Develop a model to describe that when the arrangement of objects interacting at a distance changes, different amounts of potential energy are stored in the system. (MS-PS3-2)

Energy (HS-PS3)

• Develop and use models to illustrate that energy at the macroscopic scale can be accounted for as either motions of particles or energy stored in fields. (HS-PS3-2)
• Plan and conduct an investigation to provide evidence that the transfer of thermal energy when two components of different temperature are combined within a closed system results in a more uniform energy distribution among the components in the system (second law of thermodynamics). (HS-PS3-4)

Disciplinary Core Ideas (K-12)

• Gases and liquids are made of molecules or inert atoms that are moving about relative to each other. (6-8)
• In a liquid, the molecules are constantly in contact with others; in a gas, they are widely spaced except when they happen to collide. In a solid, atoms are closely spaced and may vibrate in position but do not change relative locations. (6-8)
• Solids may be formed from molecules, or they may be extended structures with repeating subunits (6-8)
• The changes of state that occur with variations in temperature or pressure can be described and predicted using these models of matter. (6-8)
• Attraction and repulsion between electric charges at the atomic scale explain the structure, properties, and transformations of matter, as well as the contact forces between material objects. (9-12)
• The temperature of a system is proportional to the average internal kinetic energy and potential energy per atom or molecule (whichever is the appropriate building block for the system's material). The details of that relationship depend on the type of atom or molecule and the interactions among the atoms in the material. Temperature is not a direct measure of a system's total thermal energy. The total thermal energy (sometimes called the total internal energy) of a system depends jointly on the temperature, the total number of atoms in the system, and the state of the material. (6-8)
• Temperature is a measure of the average kinetic energy of particles of matter. The relationship between the temperature and the total energy of a system depends on the types, states, and amounts of matter present. (6-8)
• The amount of energy transfer needed to change the temperature of a matter sample by a given amount depends on the nature of the matter, the size of the sample, and the environment. (6-8)
• When two objects interacting through a field change relative position, the energy stored in the field is changed. (9-12)

Crosscutting Concepts (K-12)

• Cause and effect relationships may be used to predict phenomena in natural systems. (6-8)
• Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system. (9-12)
• Phenomena that can be observed at one scale may not be observable at another scale. (6-8)
• The significance of a phenomenon is dependent on the scale, proportion, and quantity at which it occurs. (9-12)
• Models can be used to represent systems and their interactions—such as inputs, processes and outputs— and energy, matter, and information flows within systems. (6-8)
• When investigating or describing a system, the boundaries and initial conditions of the system need to be defined and their inputs and outputs analyzed and described using models. (9-12)
• Complex and microscopic structures and systems can be visualized, modeled, and used to describe how their function depends on the shapes, composition, and relationships among its parts, therefore complex natural structures/systems can be analyzed to determine how they function. (6-8)
• The functions and properties of natural and designed objects and systems can be inferred from their overall structure, the way their components are shaped and used, and the molecular substructures of its various materials. (9-12)
• Explanations of stability and change in natural or designed systems can be constructed by examining the changes over time and forces at different scales. (6-8)
• Much of science deals with constructing explanations of how things change and how they remain stable. (9-12)
• Science assumes that objects and events in natural systems occur in consistent patterns that are understandable through measurement and observation. (6-8)

NGSS Science and Engineering Practices (K-12)

• Analyze and interpret data to provide evidence for phenomena. (6-8)
• Analyze data using computational models in order to make valid and reliable scientific claims. (9-12)
• Develop a model to describe unobservable mechanisms. (6-8)
• Use a model based on evidence to illustrate the relationships between systems or between components of a system. (9-12)

AAAS Benchmark Alignments (2008 Version)

4. the physical setting.

• 6-8: 4D/M1a. All matter is made up of atoms, which are far too small to see directly through a microscope.
• 6-8: 4D/M2. Equal volumes of different materials usually have different masses.
• 6-8: 4D/M3cd. In solids, the atoms or molecules are closely locked in position and can only vibrate. In liquids, they have higher energy, are more loosely connected, and can slide past one another; some molecules may get enough energy to escape into a gas. In gases, the atoms or molecules have still more energy and are free of one another except during occasional collisions.
• 6-8: 4D/M7a. No matter how substances within a closed system interact with one another, or how they combine or break apart, the total mass of the system remains the same.
• 6-8: 4D/M8. Most substances can exist as a solid, liquid, or gas depending on temperature.
• 6-8: 4E/M4. Energy appears in different forms and can be transformed within a system. Motion energy is associated with the speed of an object. Thermal energy is associated with the temperature of an object. Gravitational energy is associated with the height of an object above a reference point. Elastic energy is associated with the stretching or compressing of an elastic object. Chemical energy is associated with the composition of a substance. Electrical energy is associated with an electric current in a circuit. Light energy is associated with the frequency of electromagnetic waves.
• 9-12: 4E/H7. Thermal energy in a system is associated with the disordered motions of its atoms or molecules. Gravitational energy is associated with the separation of mutually attracting masses. Electrical potential energy is associated with the separation of mutually attracting or repelling charges.
• 9-12: 4E/H9. Many forms of energy can be considered to be either kinetic energy, which is the energy of motion, or potential energy, which depends on the separation between mutually attracting or repelling objects.
• 9-12: 4G/H2a. Electric forces acting within and between atoms are vastly stronger than the gravitational forces acting between the atoms. At larger scales, gravitational forces accumulate to produce a large and noticeable effect, whereas electric forces tend to cancel each other out.

11. Common Themes

• 6-8: 11B/M1. Models are often used to think about processes that happen too slowly, too quickly, or on too small a scale to observe directly. They are also used for processes that are too vast, too complex, or too dangerous to study.
• 6-8: 11B/M4. Simulations are often useful in modeling events and processes.
• 6-8: 11D/M3. Natural phenomena often involve sizes, durations, and speeds that are extremely small or extremely large. These phenomena may be difficult to appreciate because they involve magnitudes far outside human experience.

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%T PhET Simulation: States of Matter %D July 5, 2011 %I PhET %C Boulder %U https://phet.colorado.edu/en/simulation/states-of-matter %O application/java

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CERN Accelerating science

Seeing the invisible: Event displays in particle physics

From cloud chambers to 3D animations, physicists use a host of ingenious techniques to reveal subatomic particles too tiny to see

4 June, 2015

By Cian O'Luanaigh

This artistically enhanced image was produced by the Big European Bubble Chamber (BEBC), which started up at CERN in 1973. Charged particles passing through a chamber filled with hydrogen-neon liquid leave bubbles along their paths (Image: BEBC)

Subatomic particles are far too tiny to see, so over the years physicists have devised ingenious ways to detect and visualise them, often forming beautiful patterns and pictures in the process.  From early experiments with cloud chambers to state-of-the-art animations of Higgs-boson decays, data visualisation in particle physics has come a long way. Here are just a few of the most striking images of particle interactions - or "event displays" - from over the years.

Cloud chambers

Some detectors can reveal subatomic particles by making their tracks visible to the naked eye. The first such detector was the cloud chamber, developed in 1911 by Charles Thomson Rees Wilson  in Cambridge, UK – an invention for which he received the 1927 Nobel prize in physics.  

A cloud chamber is a box containing a supersaturated vapour. As charged particles pass through, they ionise the vapour, which condenses to form droplets on the ions. The tracks of the particles become visible as trails of droplets, which can be photographed. During the first half of the 20th century, experiments that looked at cosmic rays passing through cloud chambers revealed the existence of several fundamental particles, including the positron, the muon and the first strange particles.

Today at CERN, the Cosmics Leaving Outdoor Droplets (CLOUD) experiment uses a special cloud chamber to study the possible link between galactic cosmic rays and cloud formation. The CLOUD chamber is used both to grow the aerosol particle seeds for cloud droplets and also to form the clouds themselves. "CLOUD uses the same principle of adiabatic cooling of humid air as in the original Wilson cloud chamber," says Jasper Kirkby of the CLOUD experiment. "But the conditions are chosen to reproduce natural clouds, involving only small water-vapour supersaturations, so particle tracks do not form."

Cloud chambers can also be found at CERN's S'Cool LAB , where students build their own devices to see how charged particles can form droplets in the vapour. 

Bubble chambers

After World War II, as higher-energy particle accelerators became available, the cloud chamber was gradually replaced by the bubble chamber. Donald A. Glaser invented the bubble chamber 1952, for which he was awarded the 1960 Nobel prize in physics. It works on a similar principle to the cloud chamber, but the tracks are made visible as a trail of bubbles in a superheated liquid that is about to boil rather than in a vapour. CERN's famous bubble chamber Gargamelle was instrumental in the 1973 discovery of weak neutral currents. The discovery confirmed the prediction of such currents by electroweak theory, which treated the weak force and the electromagnetic force as different facets of the same interaction.

Bubbles of data

In cloud and bubble chambers, the data acquisition and event display were practically the same. Other (non-visual) particle detectors triggered cameras to take photographs in the chamber, and these were later projected onto a special table for analysis. At CERN in the 1960s, people worked in shifts round the clock to analyse such images, sifting through many thousands to find the events that physicists found interesting. They then measured the length and direction of the interesting particle tracks.

Watch people at work at a scanning table starting from 3:00 in this documentary about Gargamelle

However, a bubble chamber is sensitive to particles passing through only when its contents are superheated after rapid expansion. Bubbles form at this point and the chamber must be recompressed to stop the bubble growth for a picture. This limits the rate at which events can be collected. For instance, the huge Big European Bubble Chamber (BEBC), which started operation at CERN in 1973, took 6.3 million pictures during its 11 years of service. Current experiments at the Large Hadron Collider (LHC) record this number of events in less than 2 hours.

The spark chamber improved on the bubble chamber as interactions could be captured much more rapidly. In a spark chamber, particles pass through an inert gas such as neon, forming tracks. A voltage is applied to plates on alternate sides of the chamber, causing a trail of sparks to flash across the gas.

Charpak and the move to digital

Though spark chambers were faster than bubble chambers, they did not provide the detail – the resolution – that a bubble chamber could.

In 1968 at CERN, the French physicist Georges Charpak developed the “multiwire proportional chamber” to overcome the limitations of spark chambers, both in speed and their resolution. Charpak's chamber was basically a gas-filled box with a large number of parallel detector wires, each connected to individual transistor amplifiers. Now there was no need for a spark; a detector wire connected to an amplifier can detect a much smaller effect. Linked to a computer, Charpak’s chamber could achieve a counting rate a thousand times better than existing detectors.

Charpak's invention, for which he received the 1992 Nobel prize in physics, revolutionized particle detection. It made data acquisition quick, automated and electronic. As a result, it also changed the nature of event displays.

Photographs were no longer the only way to visualise particle tracks in detail; rather, event displays became visual representations of patterns of digital signals that corresponded to the particles produced in an interaction. Moreover, the event display can be made to show only those tracks that physicists find interesting. So the display has become a visual representation of the most interesting part of what happened in the detector.

As detectors became more complex and able to detect many more particles at a time, the amount of data associated with each event increased and event displays became correspondingly more intricate. Researchers developed software that could interpret the patterns of signals picked up by detectors and recreate them as images in 3D space.

The advent of computer colour screens in the late 1970s allowed physicists for the first time to render event displays in full colour, leading to discussions about which were the most suitable hues to represent different particles. Coupled with computer systems such as the Megatek, these displays could even be manipulated in 3D.

Digital data

Tom McCauley of the University of Notre Dame in the US makes event displays for the CMS experiment at CERN. "The days when data acquisition and event display were practically the same are no more," he says. "The LHC produces hundreds of millions of proton-proton collisions per second, which produce very complex events, and the detectors are correspondingly sophisticated. The displays reflect this complexity but are useful since they can provide a visual summary of what happened; you can describe geography and a route with words, but sometimes nothing beats a map with a line marking the way."

These days to create a display, experiment teams run software that converts the data into graphical objects. These graphics are then rendered in a specialised application. The details of the display – views, colours, what is shown and what is not – depend on the particular use-case.

Physicists at CERN use event displays for viewing geometry, developing algorithms and detector monitoring. The displays are also frequently used in communicating LHC science to the general public and to the media. And the images continue to become increasingly detailed.

"These days thanks to advances in computing we're capable of so much more graphics-wise and can run on many different devices and platforms," says McCauley. "I find it amazing that today I can run an event-display application on my phone!"

The nature and complexity of event displays, and even how they are generated in the first place, have changed considerably since Wilson's first cloud-chamber photos in 1911. But one thing has not changed.

"Conveying the physics accurately is always the primary consideration," says McCauley.

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Swirling Forces, Crushing Pressures Measured in the Proton

March 14, 2024

Forces push one way near the proton’s center and the opposite way near its surface.

Samuel Velasco/ Quanta Magazine

Introduction

Physicists have begun to explore the proton as if it were a subatomic planet. Cutaway maps display newfound details of the particle’s interior. The proton’s core features pressures more intense than in any other known form of matter. Halfway to the surface, clashing vortices of force push against each other. And the “planet” as a whole is smaller than previous experiments had suggested.

The experimental investigations mark the next stage in the quest to understand the particle that anchors every atom and makes up the bulk of our world.

“We really see it as opening up a completely new direction that will change our way of looking at the fundamental structure of matter,” said Latifa Elouadrhiri , a physicist at the Thomas Jefferson National Accelerator Facility in Newport News, Virginia, who is involved in the effort.

The experiments literally shine a new light on the proton. Over decades, researchers have meticulously mapped out the electromagnetic influence of the positively charged particle. But in the new research, the Jefferson Lab physicists are instead mapping the proton’s gravitational influence — namely, the distribution of energies, pressures and shear stresses throughout, which bend the space-time fabric in and around the particle. The researchers do so by exploiting a peculiar way in which pairs of photons, particles of light, can imitate a graviton, the hypothesized particle that conveys the force of gravity. By pinging the proton with photons, they indirectly infer how gravity would interact with it, realizing a decades-old dream of interrogating the proton in this alternative way.

“It’s a tour de force,” said Cédric Lorcé , a physicist at the Ecole Polytechnique in France who was not involved in the work. “Experimentally, it’s extremely complicated.”  

From Photons to Gravitons

Physicists have learned a tremendous amount about the proton over the last 70 years by repeatedly hitting it with electrons. They know that its electric charge extends roughly 0.8 femtometers, or quadrillionths of a meter, from its center. They know that incoming electrons tend to glance off one of three quarks — elementary particles with fractions of charge — that buzz about inside it. They have also observed the deeply strange consequence of quantum theory where, in more forceful collisions, electrons appear to encounter a frothy sea made up of far more quarks as well as gluons, the carriers of the so-called strong force, which glues the quarks together.

All this information comes from a single setup: You fire an electron at a proton, and the particles exchange a single photon — the carrier of the electromagnetic force — and push each other away. This electromagnetic interaction tells physicists how quarks, as charged objects, tend to arrange themselves. But there is a lot more to the proton than its electric charge.

Latifa Elouadrhiri, a senior staff scientist at Jefferson Laboratory, led the collecting of data from which she and her collaborators are now calculating mechanical properties of the proton.

Courtesy of Latifa Elouadrhiri

“How are matter and energy distributed?” asked Peter Schweitzer , a theoretical physicist at the University of Connecticut. “We don’t know.”

Schweitzer has spent most of his career thinking about the gravitational side of the proton. Specifically, he’s interested in a matrix of properties of the proton called the energy-momentum tensor. “The energy-momentum tensor knows everything there is to be known about the particle,” he said.

In Albert Einstein’s theory of general relativity, which casts gravitational attraction as objects following curves in space-time, the energy-momentum tensor tells space-time how to bend. It describes, for instance, the arrangement of energy (or, equivalently, mass) — the source of the lion’s share of space-time twisting. It also tracks information about how momentum is distributed, as well as where there will be compression or expansion, which can also lightly curve space-time.

If we could learn the shape of space-time surrounding a proton, Russian and American physicists independently worked out in the 1960s, we could infer all the properties indexed in its energy-momentum tensor. Those include the proton’s mass and spin, which are already known, along with the arrangement of the proton’s pressures and forces, a collective property physicists refer to as the “Druck term,” after the word for pressure in German. This term is “as important as mass and spin, and nobody knows what it is,” Schweitzer said — though that’s starting to change.

In the ’60s, it seemed as if measuring the energy-momentum tensor and calculating the Druck term would require a gravitational version of the usual scattering experiment: You fire a massive particle at a proton and let the two exchange a graviton — the hypothetical particle that makes up gravitational waves — rather than a photon. But due to the extreme weakness of gravity, physicists expect graviton scattering to occur 39 orders of magnitude more rarely than photon scattering. Experiments can’t possibly detect such a weak effect.

“I remember reading about this when I was a student,” said Volker Burkert , a member of the Jefferson Lab team. The takeaway was that “we probably will never be able to learn anything about mechanical properties of particles.”

Gravity Without Gravity

Gravitational experiments are still unimaginable today. But research in the late 1990s and early 2000s by the physicists Xiangdong Ji and, working separately, the late Maxim Polyakov revealed a workaround .

The general scheme is the following. When you fire an electron lightly at a proton, it usually delivers a photon to one of the quarks and glances off. But in fewer than one in a billion events, something special happens. The incoming electron sends in a photon. A quark absorbs it and then emits another photon a heartbeat later. The key difference is that this rare event involves two photons instead of one — both incoming and outgoing photons. Ji’s and Polyakov’s calculations showed that if experimentalists could collect the resulting electron, proton and photon, they could infer from the energies and momentums of these particles what happened with the two photons. And that two-photon experiment would be essentially as informative as the impossible graviton-scattering experiment.

Merrill Sherman/ Quanta Magazine

How could two photons know anything about gravity? The answer involves gnarly mathematics. But physicists offer two ways of thinking about why the trick works.

Photons are ripples in the electromagnetic field, which can be described by a single arrow, or vector, at each location in space indicating the field’s value and direction. Gravitons would be ripples in the geometry of space-time, a more complicated field represented by a combination of two vectors at every point. Capturing a graviton would give physicists two vectors of information. Short of that, two photons can stand in for a graviton, since they also collectively carry two vectors of information.

An alternative interpretation of the math goes as follows. During the moment that elapses between when a quark absorbs the first photon and when it emits the second, the quark follows a path through space. By probing this path, we can learn about properties like the pressures and forces that surround the path.

“We are not doing a gravitational experiment,” Lorcé said. But “we should obtain indirect access to how a proton should interact with a graviton.”  

Probing Planet Proton

The Jefferson Lab physicists scraped together a few two-photon scattering events in 2000. That proof of concept motivated them to build a new experiment, and in 2007, they smashed electrons into protons enough times to amass roughly 500,000 graviton-mimicking collisions. Analyzing the experimental data took another decade.

From their index of space-time-bending properties, the team extracted the elusive Druck term, publishing their estimate of the proton’s internal pressures in Nature in 2018.

They found that in the heart of the proton, the strong force generates pressures of unimaginable intensity — 100 billion trillion trillion pascals, or about 10 times the pressure at the heart of a neutron star. Farther out from the center, the pressure falls and eventually turns inward, as it must for the proton not to blow itself apart. “This comes out of the experiment,” Burkert said. “Yes, a proton is actually stable.” (This finding has no bearing on whether protons decay , however, which involves a different type of instability predicted by some speculative theories.)

The Jefferson Lab group continued to analyze the Druck term. They released an estimate of the shear forces — internal forces pushing parallel to the proton’s surface — as part of a review published in December . The physicists found that close to its core, the proton experiences a twisting force that gets neutralized by a twisting in the other direction nearer the surface. These measurements also underscore the particle’s stability. The twists had been expected based on theoretical work from Schweitzer and Polyakov. “Nonetheless, witnessing it emerging from the experiment for the first time is truly astounding,” Elouadrhiri said.

Now they’re using these tools to calculate the proton’s size in a new way. In traditional scattering experiments, physicists had observed that the particle’s electric charge extends about 0.8 femtometers from its center (that is, its constituent quarks buzz about in that region). But that “charge radius” has some quirks. In the case of the neutron, for instance — the proton’s neutral counterpart, in which two negatively charged quarks tend to hang out deep inside the particle while one positively charged quark spends more time near the surface — the charge radius comes out as a negative number. “It doesn’t mean the size is negative; it’s just not a faithful measure,” Schweitzer said.

The new approach measures the region of space-time that’s significantly curved by the proton. In a preprint that has not yet been peer reviewed, the Jefferson Lab team calculated that this radius may be about 25% smaller than the charge radius, just 0.6 femtometers.

Planet Proton’s Limits

Conceptually, this kind of analysis smooths out the blurry dance of quarks into a solid, planetlike object, with pressures and forces acting on each speck of volume. That frozen planet does not fully reflect the raucous proton in all its quantum glory, but it’s a useful model. “It’s an interpretation,” Schweitzer said.

And physicists stress that the initial maps are rough, for a few reasons.

First, precisely measuring the energy-momentum tensor would require much higher collision energies than Jefferson Lab can produce. The team has worked hard to carefully extrapolate trends from the relatively low energies they can access, but physicists remain unsure how accurate these extrapolations are.

As a student, Volker Burkert read that directly measuring the gravitational properties of the proton was impossible. Today he participates in a collaboration at Jefferson Laboratory that’s in the process of teasing out those same properties indirectly.

Thomas Jefferson National Accelerator Facility

Moreover, the proton is more than its quarks; it also contains gluons, which slosh around with their own pressures and forces. The two-photon trick cannot detect gluons’ effects. A separate team at Jefferson Lab used an analogous trick (involving a double-gluon interaction) to publish a preliminary gravitational map of these gluon effects in Nature last year , but it too was based on limited, low-energy data.

“It’s a first step,” said Yoshitaka Hatta, a physicist at Brookhaven National Laboratory who was inspired to start studying the gravitational proton after the Jefferson Lab group’s 2018 work.

Sharper gravitational maps of both the proton’s quarks and its gluons may come in the 2030s when the Electron-Ion Collider, an experiment currently under construction at Brookhaven, will begin operations.

In the meantime, physicists are pushing ahead with digital experiments. Phiala Shanahan , a nuclear and particle physicist at the Massachusetts Institute of Technology, leads a team that computes the behavior of quarks and gluons starting from the equations of the strong force. In 2019, she and her collaborators estimated the pressures and shear forces, and in October, they estimated the radius , among other properties. So far, their digital findings have broadly aligned with Jefferson Lab’s physical ones. “I am certainly quite excited by the consistency between recent experimental results and our data,” Shanahan said.

Even the blurry glimpses of the proton attained so far have gently reshaped researchers’ understanding of the particle.

Some consequences are practical. At CERN, the European organization that runs the Large Hadron Collider, the world’s largest proton smasher, physicists had previously assumed that in certain rare collisions, quarks could be anywhere within the colliding protons. But the gravitationally inspired maps suggest that quarks tend to hang out near the center in such cases.

“Already the models they use at CERN have been updated,” said Francois-Xavier Girod, a Jefferson Lab physicist who worked on the experiments.

The new maps may also offer guidance toward resolving one of the deepest mysteries of the proton: why quarks bind themselves into protons at all. There’s an intuitive argument that because the strong force between each pair of quarks intensifies as they get further apart, like an elastic band, quarks can never escape from their comrades.

But protons are made from the lightest members of the quark family. And lightweight quarks can also be thought of as lengthy waves extending beyond the proton’s surface. This picture suggests that the binding of the proton may come about not through the internal pulling of elastic bands but through some external interaction between these wavy, drawn-out quarks. The pressure map shows the attraction of the strong force extending all the way out to 1.4 femtometers and beyond, bolstering the argument for such alternative theories.

“It’s not a definite answer,” Girod said, “but it points toward the fact that these simple images with elastic bands are not relevant for light quarks.”

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Thermal Energy Particle Motion Experiment

How does adding thermal energy affect the particle motion of a gas? 

Ngss alignment: ms-ps3-4.

The disciplinary core idea behind this standard is PS3.A: Definitions of Energy and PS3.B: Conservation fo Energy and Energy Transfer. In PS3 the standard specifically looks at how temperature is a measure of the average kinetic energy of the particles of matter. This leads to the conclusion that the temperature and the total energy of a system depend on the type, states, and the amounts of matter present. In PS3.B, it specifically looks at how the amount of energy needed to change the temperature of a sample of matter depends on the nature of the matter, the size of the sample and the environment. The setup of this lab provides a unique way to investigate this standard by gathering data on the energy of a sample of matter both with a direct measure of temperature and an indirect measurement of the movement of the particles (kinetic energy) using a barometric pressure sensor. By placing a PocketLab Voyager or Weather with a PocketLab attachable temperature probe inside a mason jar, temperature and pressure can be simultaneously measured. By adding thermal energy with a heat lamp, the particles get more excited and move around more quickly, creating additional pressure inside the jar, measured by PocketLab's barometric pressure sensor. The attachable temperature probe will also directly measure the changing temperature inside the jar. This is a great example of the specific parts of PS3.A under this standard. Students can then use the Science and Engineering Practice, Planning and Carrying out an Investigation, to examine the specific pars of PS3.B in this standard. Students can find ways to amount of matter in the jar, by either trying a different size jar or by trying to remove air from the jar. They can also change the material holding the matter (e.g. change the jar to a plastic container). In their investigation, students would see compare how these changes would affect the energy transfer measured by the Pocketlab.  MS-PS3-4:  Plan an investigation to determine the relationships among the energy transferred the type of matter, the mass, and the change in the average kinetic energy of the particles as measured by the temperature of the sample. 

The standard is broken down into the three NGSS pillars below: Science and Engineering Practices  - Planning and Carrying Out Investigations Disciplinary Core Ideas  - PS3.A Definitions of Energy and PS3.B: Conservation fo Energy and Energy Transfer Crosscutting Concepts  - Scale, Proportion, and Quantity 

Thermal Energy Examples

Matter makes up everything around us. The air we breathe, the water we drink, the chair we are sitting on, the cells in our body, it is all made up of matter. Matter can exist in different states: Take water for example, it can exist as a solid (an ice cube), liquid (water in a cup for drinking), and gas  (vapor rising from a boiling pot of water). In all three states, water is always made of the same molecules, H20, and the difference is the amount of thermal energy. Water is a good example of these three states because it can easily transition between them with relatively small changes in thermal energy. 

What is temperature ? 

Temperature can be described as a measurement of the average kinetic energy in the matter in a substance. Kinetic energy is energy from motion. Matter that is moving around slowly has less kinetic energy. Matter that is moving around more quickly has greater kinetic energy. By measuring temperature, you can understand how much kinetic energy a substance has. 

Three types of thermal energy transfer:

The three types of thermal energy transfer are conduction, convection and radiation. Conduction involves direct contact of atoms, convection involves the movement of warm particles and radiation involves the movement of electromagnetic waves. In our experiment, we will use the radiation from a heat lamp.

Pressure of a gas:

In a sealed container, the pressure of the gas is the amount of force that the particles in the gas are pushing out on the container.  

Objective - Develop a Model for Thermal Energy Transfer 

Students will be able to: 

• Develop a model that predicts how adding thermal energy will affect the motion of the matter in a substance.  
• Provide evidence for that model by collecting data on particle motion using PocketLab’s barometric pressure sensor. 
• Use the model to answer the investigation question and predict the relative kinetic energy in a substance when it is a solid, liquid, or gas. 

Thermal Energy Investigation Questions

Your investigation will answer the following questions: 

• In a sealed container, how are the temperature of a gas and the pressure of that gas related? 
• How does adding thermal energy affect the particle motion of a gas?

What do you predict the answers to the Investigation Questions will be? Explain using your own prior knowledge or information from the Background Information section. 

• PocketLab Voyager or PocketLab One
• Canning/Mason Jar with a sealable lid
• Heat Lamp (or bunsen burner)

Before beginning the activity, make sure to wear safety goggles, and follow all safety precautions instructed by your teacher. The heat source (heat lamp or bunsen burner) can get very hot and cause injury or fires. 

Procedure: Plan Your Investigation

• Connect your PocketLab to PocketLab mobile app or the PocketLab web app. 
• Place the PocketLab in the canning jar and seal the jar. 

Your procedure will need a step-by-step guide of how your group will answer the Investigation Questions.  In your procedure, be sure to answer the following questions: 

• What type of PocketLab data do you need to collect to develop your model? (Remember you can view two graphs at the same time). 
• What is the independent variable, what is the dependent variable, and what are the control variables in your investigation? 
• How will the independent variable be changed and how will the dependent variable be measured? 
• How will the Data Analysis tools in the PocketLab App help in analyzing the results of each trial? 
• How many Runs and Trials are needed to answer the Investigation Question? 
• How will you visualize your data for analysis (table, graph, etc.)? 

Data Analysis Tools 

To use the Data Analysis tools in the PocketLab Web App, on a recorded data trial, highlight the portion of the graph that you are interested in by clicking and dragging with your mouse. Next, click the Data Analysis button. You should see basic statistics on the portion of the graph you’re viewing as well as the ability to add curve fits. 

Data Analysis Part 1

Follow your procedure for analyzing the results of each Trial and Run then answer the following questions: 

• What did the collected data tell you about the Investigation Question? 
• How did use the Data Analysis Tools and your data visualization help you determine the answer to the above question? 

Data Analysis Part 2: Develop a Thermal Energy Transfer Model

Pick 5 temperature and pressure readings at different times during your trial. Draw a diagram that modes the particle motion of the gas in the container at each of those different points. Be sure your model illustrates how the kinetic energy of the particles is affecting by the different levels of thermal energy. 

Develop a Model Extension Describe how you could predict the change in pressure in a gas (of normal atmosphere) if the temperature changes by x degrees. Use the data you collected in your investigation to create your model. 

HINT: To create your model, try graphing data from your pressure readings against data from your temperature readings. (You don’t need to graph every data point. Use data points that are evenly spaced out during the course of your trial). What do you notice? Can you fit a line to that data? What is the equation for that line? How would that help you Develop a Model? 

Claim Were your hypotheses valid or invalid? How are the temperature of a gas and the pressure of that gas related? How does adding thermal energy affect the particle motion of a gas? 

Evidence How do your analysis of the collected data and the model you developed support your claim? 

Justification of Evidence What scientific concepts or principles can explain the evidence? 

Further Discussion

Predict: How does the kinetic energy of the molecules in a substance relate to the state of that substance (solid, liquid, or gas)? Even though you only investigated the particle motion of a gas, how does the data you collected support your answer? 

• PocketLab Voyager
• PocketLab One

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• 13 June 2023
• Correction 20 June 2023

Particle, wave, both or neither? The experiment that challenges all we know about reality

• Anil Ananthaswamy 0

Anil Ananthaswamy is a writer based in California, and author of Through Two Doors at Once .

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The double-slit experiment’s interference patterns suggest something is in two places at once. Credit: Huw Jones/Getty

Thomas Young, born 250 years ago this week, was a polymath who made seminal contributions in fields from physics to Egyptology . But perhaps his most enduring legacy is proving Isaac Newton wrong about light — and igniting a debate about the nature of reality that still persists.

“The experiments I am about to relate”, he told the Royal Society of London 1 on 24 November 1803, “may be repeated with great ease, whenever the sun shines.” In a simple, modern form, Young’s ‘double-slit’ experiment involves shining light of a single frequency (say, from a red laser) through two fine, parallel openings in an opaque sheet, onto a screen beyond. If light were made of streams of particles, as Newton conjectured, you would expect to see two distinct strips of light on the screen, where the particles pile up after travelling through one slit or the other. But that’s not what happens. Instead, you see many bands of light and dark, strung out in stripes like a barcode: an interference pattern (see ‘Wave–particle weirdness’).

Interference is possible only if light behaves as a wave that strikes both slits at once and diffracts through each, creating two sets of waves on the other side of the slits that propagate towards the screen. Where the crest of one wave overlaps with the crest of the other, you get constructive interference and a patch of light. Where a crest meets a trough, you get destructive interference and darkness.

It’s hard to overstate how wild this discovery was to physicists in Young’s time. But the wildness truly began when Max Planck and Albert Einstein laid the foundations for quantum mechanics in the early twentieth century. Today, quantum mechanics forms a peerlessly accurate framework to explain the basic elements of material reality and their interactions. Pretty early on, it became clear that it implied that light is made of indivisible units of energy called photons — particles, in fact. The amount of energy each carried was proportional to the frequency of the light. Some carry enough of a wallop to knock electrons off atoms of metal, giving us the photoelectric effect that enables today’s solar cells. (It was the study of this effect that led Einstein to his conclusions about light’s particulate nature.)

With the emergence of quantum mechanics, the idea of light as a wave faced a challenge. But it wasn’t as simple as going back to the particle view. Further tests of quantum theory using the double-slit experiment only deepened the mystery. And it hasn’t been solved yet.

Singularly quantum

Imagine, now, that your light source can shoot individual photons of red light at the two slits, while guaranteeing that only one photon goes through the apparatus at any time. A photographic plate on the other side records where the photons land. Classical intuition says each photon can go through only one slit or the other. So, this time, we should see photons accumulating over time and forming two strips of light on the photographic plate. Yet the mathematics of quantum theory implied that the interference pattern would persist.

It was several decades before the technology matured enough to verify these predictions experimentally, using more complex set-ups that were in principle the double-slit. At first, it wasn’t done with photons, but with electrons — entities that we know as particles, but that quantum mechanics predicts act as waves, too. Then, in the 1980s, a team led by Alain Aspect at the Optical Institute in Palaiseau, France, performed the double-slit experiment with single photons 2 . Quantum theory won out: an interference pattern emerged, even when only single particles passed through the slits.

‘Spooky’ quantum-entanglement experiments win physics Nobel

Aspect won a share of the 2022 Nobel prize in physics for his contribution to confirming the predictions of quantum mechanics through experiment. But such experiments leave matters of interpretation wide open. There is simply no way to comprehend what’s happening with minds attuned to the classical world of everyday objects.

When it comes to the double-slit experiment, quantum mechanics does tell a form of story. It says that a photon’s position is described by a mathematical abstraction called the wavefunction — which, as the name suggests, behaves like a wave. This wavefunction, mathematically speaking, hits the two slits, diffracts into two sets of waves and recombines to create the interference pattern. The value of the wavefunction at any location on the photographic plate lets you calculate the probability of finding the photon there. The probability is very high in regions of constructive interference, and very low in regions of destructive interference.

In a sense, then, a photon or any other quantum object acts like both a particle and a wave. This ‘wave–particle duality’ embodies many of the central conceptual mysteries of quantum mechanics that are unresolved to this day. Even if you could know everything about a photon’s initial state, there’s no way to tell exactly where it’ll land on the detector. You have to talk in terms of probabilities given by the wavefunction. These probabilities are borne out only when thousands or tens of thousands of photons are sent through the double slit, one by one.

Before the measurement — in this case, detection by the photographic plate — the mathematics says the particle exists in a superposition of states: in a sense, it has taken both paths, through the right slit and the left. Standard quantum mechanics says that the wavefunction ‘collapses’ when measured, and that the act of observation in some way precipitates that collapse. Before this, the photon has a finite probability of being found in many different regions, but on measurement, the wavefunction peaks at the location in which the photon appears (the probability there equals 1) and is nullified everywhere else (probability equals 0).

It gets even odder. If you can determine which path the photon took on its way to the detector, it acts like a particle that does indeed go through one slit or the other: the interference pattern disappears. But if you cannot glean this ‘which-way’ information, the photon acts like a wave. Whenever there are two or more ways for a photon — or, indeed, any quantum object — to get to a final state, quantum interference occurs.

What’s a wavefunction?

But to generate interference, something has to go through — or at least interact in some way with — both slits. In the mathematics, the wavefunction does the job. Some physicists would say that the wavefunction simply represents information about the quantum system and is not real — in which case it’s hard to explain what interacts with both slits at once. But you can explain the interference pattern if you consider the wavefunction to be real.

This creates its own problems. Imagine a real wavefunction that spreads for kilometres and kilometres before an observer detects the photon. At this point, the wavefunction peaks at the photon’s location, and simultaneously drops to zero everywhere else — over a large, macroscopic distance. This suggests a kind of instantaneous, non-local influence that bothered Einstein no end. One can avoid this with interpretations of quantum theory that don’t collapse the wavefunction, but that opens other cans of worms.

Thomas Young reported the results of the original double-slit experiment in the early nineteenth century. Credit: Photo Researchers/SPL

Perhaps the most notorious is the many-worlds interpretation, the brainchild of US physicist Hugh Everett in the 1950s. This argues that every possible event — in the case of the double slit, a particle going through the left and the right slit — happens, each in its own world. There is no collapse: measurement simply reveals the state of the quantum system in that world. Detractors ask how it’s possible to justify this constant proliferation of worlds, and how, in a many-worlds framework, you can explain why measuring quantum systems yields probabilities, given that there are always definite outcomes in each world.

The de Broglie–Bohm theory, named after quantum pioneers Louis de Broglie and David Bohm, provides another alternative. It says that particles exist with definite positions and momenta, but are guided by an all-encompassing, invisible ‘pilot’ wave, and it’s this wave that goes through both slits. The most profound implication of this theory, that everything is linked to everything else in the Universe by the underlying pilot wave, is one many physicists have trouble accepting.

In the 1970s and 1980s, physicists upgraded the double-slit experiment to seek clarity about the nature of quantum reality, and the perplexing role observation apparently has in collapsing a defined, classical reality out of it. Most notably, John Wheeler at the University of Texas at Austin designed the ‘delayed choice’ thought experiment 3 . Imagine a double-slit set-up that gives the option of gathering or ignoring information about which way the particle went. If you ignore the ‘which-way’ information, you get wave-like behaviour; if you don’t, you get particle-like patterns.

Superconducting qubits cover new distances

With the apparatus on the ‘collect which-way information’ setting, send a photon through the double slits. It should act like a particle and go through one slit or the other. But just before the photon lands on the detector, flip the apparatus to ignore the which-way information. Will the photon, until then supposedly a particle, suddenly switch to being a wave?

Decades later, Aspect’s team performed this experiment with single photons and showed that the answer is yes 4 . Even if the photon had ostensibly travelled through the entire set-up as a particle, switching the apparatus setting so that it ignored which-way information caused it to act like a wave. Did the photon travel back in time and come back through the two slits as a wave? To avoid such nonsensical explanations, Wheeler argued that the only way to make sense of the experiment was to say that the photon has no reality — it’s neither wave nor particle — until it’s detected.

Back in the 1980s, Marlan Scully, then at the University of New Mexico in Albuquerque, and his colleagues came up with a similarly befuddling thought experiment 5 . They imagined collecting the which-way information about a photon by using a second photon ‘entangled’ with the first — a situation in which measuring the quantum state of one tells you about the quantum state of the other. As long as the which-way information can in principle be extracted, the first photon should act like a particle. But if you erase the information in the entangled partner, the mathematics showed, the first photon goes back to behaving like a wave. In 2000, Scully, Yoon-Ho Kim and their colleagues reported performing this experiment 6 . Surprisingly — or unsurprisingly, by this stage — intuition was once again defeated and quantum weirdness reigned supreme.

Larger and still larger

Others are still pushing the double slit in new directions. This year, Romain Tirole at Imperial College London and his colleagues described an experiment in which the slits were temporal: one slit was open at one point in time and the second slit an instant later 7 . A beam of light that goes through these temporal slits produces an interference pattern in its frequency spectrum. Again, the mathematics predicts exactly this behaviour, so physicists aren’t surprised. But it is more proof that the double-slit experiment highlights the lacunae in our understanding of reality, a quarter of a millennium after the birth of the man who devised it.

The double-slit experiment’s place in the pantheon of physics experiments is assured. But it would be further cemented if and when physicists using it were able to work out which theory of the quantum world is correct.

For example, some theories posit that quantum systems that grow bigger than a certain, as-yet-undetermined size randomly collapse into classical systems, with no observer needed. This would explain why macroscopic objects around us don’t obviously work according to quantum rules — but how big does something have to be before it stops acting in a quantum way?

In 2019, Markus Arndt and Yaakov Fein at the University of Vienna and their colleagues reported sending macromolecules called oligoporphyrins, composed of up to 2,000 atoms, through a double slit to see whether they produce an interference pattern 8 . They do, and these patterns can be explained only as a quantum phenomenon. Arndt’s team and others continue to push such experiments to determine whether a line exists between the quantum and the classical world.

Last year, Siddhant Das at the Ludwig Maximilian University of Munich, Germany, and his colleagues analysed the double-slit experiment in the context of the de Broglie–Bohm theory 9 . Unlike standard quantum mechanics, this predicts not just the distribution of particles on the screen that leads to the spatial interference pattern, but also the distribution of when the particles arrive at the screen. The researchers found that their calculations on the distribution of arrival times agreed qualitatively with observations made two decades before, in a double-slit experiment using helium atoms 10 . But it was difficult to prove their case definitively. They are awaiting better data from a similar double-slit experiment done with current technology, to see whether it matches predictions.

And so it goes on, a world away from anything Young or his peers at the Royal Society could have conceived of more than two centuries ago. “Thomas Young would probably scratch his head if he could see the status of today’s experiments,” says Arndt. But that’s because his experiment, so simple in concept, has left us scratching our heads to this day.

Nature 618 , 454-456 (2023)

doi: https://doi.org/10.1038/d41586-023-01938-6

Updates & Corrections

Correction 20 June 2023 : An earlier version of the second picture caption gave the wrong date for when Young reported results of a double-slit experiment.

Young, T. Phil. Trans. R. Soc. 94 , 1–16 (1804).

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Grangier, P., Roger, G. & Aspect, A. Europhys. Lett. 1 , 173 (1986).

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Miller, W. A. & Wheeler, J. A. Foundations of Quantum Mechanics in the Light of New Technology (Eds Nakajima, S., Murayama, Y. & Tonomura, A.) 72–84 (World Scientific, 1997).

Jacques, V. et al. Science 315 , 966–968 (2007).

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Scully, M. O. & Drühl, K. Phys. Rev. A. 25 , 2208 (1982).

Kim, Y.-H. et al. Phys. Rev. Lett. 84 , 1 (2000).

Tirole, R. et al. Nature Phys . https://doi.org/10.1038/s41567-023-01993-w (2023).

Fein, Y. Y. et al. Nature Phys. 15 , 1242–1245 (2019).

Das, S., Deckert, D.-A., Kellers, L. & Struyve, W. Preprint at https://arxiv.org/abs/2211.13362 (2022).

Kurtsiefer, Ch., Pfau T. & Mlynek, J. Nature 386 , 150–153 (1997).

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The author declares no competing interests.

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Theory of particle beams transport over curved plasma-discharge capillaries

A. frazzitta, r. pompili, and a. r. rossi, phys. rev. accel. beams 27 , 091301 – published 13 september 2024.

• No Citing Articles
• INTRODUCTION
• ABP SINGLE PARTICLE AND BEAM DYNAMICS
• NUMERICAL SIMULATIONS
• CONCLUSIONS
• ACKNOWLEDGMENTS

We present a new approach that demonstrates the deflection and guiding of relativistic electron beams over curved paths by means of the magnetic field generated in a plasma-discharge capillary. The active bending plasma (ABP) represents a promising solution that has been recently demonstrated with a proof of principle experiment. An ABP device consists of a curved capillary where large discharges (of the order of kA) are propagated in a plasma channel. Unlike conventional bending magnets, in which the field is constant over the bending plane, in the ABP, the azimuthal magnetic field generated by the discharge grows with the distance from the capillary axis. This features makes the device less affected by the beam chromatic dispersion so that it can be used to efficiently guide particle beams with non-negligible energy spreads. The study we present in the following aims to provide a theoretical basis of the main ABP features by presenting an analytical description of a single-particle motion and rms beam dynamics. The retrieved relationships are verified by means of numerical simulations and provide the theoretical matrix formalism needed to completely characterize such a new transport device.

• Received 7 May 2024
• Accepted 20 August 2024

DOI: https://doi.org/10.1103/PhysRevAccelBeams.27.091301

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

• Research Areas
• Physical Systems

Authors & Affiliations

• 1 University of Rome Sapienza , Piazzale Aldo Moro 5, 00185 Rome, Italy
• 2 Laboratori Nazionali di Frascati , Via Enrico Fermi 54, 00044 Frascati, Italy
• 3 INFN Milano , via Celoria 16, 20133 Milan, Italy

Article Text

Vol. 27, Iss. 9 — September 2024

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ABP magnetic field: field amplitude as a function of distance from the axis of the capillary: comparison between a realistic discharge field [ 10 ] (blue) and the current-equivalent Biot-Savart type field (orange). Note that the discharge field tends to a linear behavior near capillary axis.

ABP reference system: (a) capillary render and coordinates: ρ c , bending radius; r c , capillary section radius; s , curvilinear coordinate along the capillary axis; and θ , bending angle. In orange, a sketch of the ABP bent capillary with a detail on transverse section. (b) Beam particle coordinates represented on capillary transverse section: Cartesian reference system ( x , y ) with origin centered on the beam mean equilibrium radius ρ 0 , associated with the magnetic field B 0 satisfying the beam rigidity equation. In orange, capillary circular inner boundary.

Minimum required current I lim as computed from Eq. ( 3 ) as a function of beam energy, for several r c / ρ c ratio values.

ABP and CBM dispersion functions comparison, as computed from Eq. ( 8 ), for ρ 0 = 1 and k x = 10 . The dispersion amplitude difference is on the order of O ( 10 2 ) , while the period difference is O ( 10 1 ) . In the detail window below can be observed the same exact trend of the two dispersions for bending lengths s ≲ λ x / 4 : indeed, the ratio between ABP and CBM dispersion is given by a sinc function in Eq. ( 10 ) that tends to 1 for s → 0 .

ABP transition: (a) 1–6 transition space for a whole beam above transition, where regions corresponding to faster (slower) states relative to the reference trajectory are highlighted in green (blue). The presence of finite emittance broadens the transition hyperbola (orange), resulting in an excess of states at Δ s < 0 (slower beam centroid); (b)  γ T limit, with possible γ T values as a function of beam energy (abscissa), where it can be observed that for γ < ρ c / r c (dashed black line), the beam will be constrained below the transition.

Beam rms elongation plotted versus beam Lorentz factor γ and transition Lorentz factor γ T from Eq. ( 18 ). Transition line γ = γ T is shown in solid red. Minimal elongation is shown in solid white. The orange region shows out-of-use configurations, where I < I lim [see Eq. ( 3 )]. The presented case features σ Δ γ / γ = 0.01 and ε n = 1     mm   mrad . After some threshold energy given by emittance and energy spread, the optimal condition is found above transition. This knowledge may be relevant in ultrashort beam applications.

Transverse and longitudinal beam dynamics. Comparison between numerical and analytical solutions for 50 MeV beams. (a) Numerical rectified trajectories in bending plane, comparison between optical (upper plot, mismatched beam, no energy spread) and dispersive (lower plot, matched beam, 1% energy spread) envelope oscillations. As expected, optical oscillations happen at double frequency compared to dispersive ones. Red dashed line shows expected equilibrium radius Eq. ( 2 ). In the dispersive case, note the slight misalignment between oscillation extremes, due to the energy dependence of k x ; (b) scatter plot of deviation from the reference trajectory at the end of the evolution of an initially pointlike beam in the longitudinal coordinate and with γ > γ T , σ Δ γ / γ = 0.01 , and ε n = 10     mm   mrad . The color bar shows the amplitude of each particle’s betatron oscillation, showing a clear correlation with delay respect to reference trajectory.

(a) ABP/CBM transverse spot ratio as a function of device length, evaluated for several σ Δ γ / γ . Dashed line shows expected behavior given by Eq. ( 11 ), which works properly for greater spot oscillations (e.g., 10% case). (b) Beam rms elongation as a function of energy spread, plotted for matched beams in a wide emittance range. Aspect ratio is set to unity in all cases. Dashed lines are given by Eq. ( 18 ) and show good agreement with numerics.

Transverse rms size saturation with increasing offset with respect to the equilibrium radius Δ x inj = 0 , 0.3     mm (a), (b). The beam is injected with a double rms size compared to matching, to better observe saturation in case (a). The full blue lines depict the numerical evolution of beam size, while dashed lines represent analytical predictions. The dashed red line indicates the saturation length calculated using Eq. ( 21 ), and the dashed black line represents the saturation value from Eq. ( c7 ).

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