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Maxwell–Boltzmann distribution

Maxwell–Boltzmann distribution is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Maxwell–Boltzmann distribution rather than just read about it. In short: In physics (in particular in statistical mechanics), the Maxwell–Boltzmann distribution, or Maxwell(ian) distribution, is a particular probability distribution named after James Clerk Maxwell and Ludwig Boltzmann. It was first defined and used for describing particle speeds in idealized gases, where the particles move freely inside a stationary container without interacting with one another, except for very brief co…

Maxwell–Boltzmann distribution — main illustration
Maxwell–Boltzmann distribution — illustration

Key takeaways

  • Maxwell–Boltzmann distribution belongs to physics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Maxwell–Boltzmann distribution to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Maxwell–Boltzmann distribution from memory before moving on to harder problems.

Reference excerpt

In physics (in particular in statistical mechanics), the Maxwell–Boltzmann distribution, or Maxwell(ian) distribution, is a particular probability distribution named after James Clerk Maxwell and Ludwig Boltzmann. It was first defined and used for describing particle speeds in idealized gases, where the particles move freely inside a stationary container without interacting with one another, except for very brief collisions in which they exchange energy and momentum with each other or with their thermal environment. The term "particle" in this context refers to gaseous particles only (atoms or molecules), and the system of particles is assumed to have reached thermodynamic equilibrium. The energies of such particles follow what is known as Maxwell–Boltzmann statistics, and the statistical distribution of speeds is derived by equating particle energies with kinetic energy. Mathematically, the Maxwell–Boltzmann distribution is the chi distribution with three degrees of freedom (the components of the velocity vector in Euclidean space), with a scale parameter measuring speeds in units proportional to the square root of T / m {\displaystyle T/m} (the ratio of temperature and particle mass). The Maxwell–Boltzmann distribution is a result of the kinetic theory of gases, which provides a simplified explanation of many fundamental gaseous properties, including pressure and diffusion. The Maxwell–Boltzmann distribution applies fundamentally to particle velocities in three dimensions, but turns out to depend only on the speed (the magnitude of the velocity) of the particles. A particle speed probability distribution indicates which speeds are more likely: a randomly chosen particle will have a speed selected randomly from the distribution, and is more likely to be within one range of speeds than another. The kinetic theory of gases applies to the classical ideal gas, which is an idealization of real gases. In real gases, there are various effects (e.g., van der Waals interactions, vortical flow, relativistic speed limits, and quantum exchange interactions) that can make their speed distribution different from the Maxwell–Boltzmann form. However, rarefied gases at ordinary temperatures behave very nearly like an ideal gas and the Maxwell speed distribution is an excellent approximation for such gases. This is also true for ideal plasmas, which are ionized gases of sufficiently low density. The distribution was first derived by Maxwell in 1860 on heuristic grounds. Boltzmann later, in the 1870s, carried out significant investigations into the physical origins of this distribution. The distribution can be derived on the ground that it maximizes the entropy of the system. A list of derivations are:

Maximum entropy probability distribution in the phase space, with the constraint of conservation of average energy ⟨ H ⟩ = E ; {\displaystyle \langle H\rangle =E;}

Canonical ensemble.

Distribution function For a system containing a large number of identical non-interacting, non-relativistic classical particles in thermodynamic equilibrium, the fraction of the particles within an infinitesimal element of the three-dimensional velocity space d 3v, centered on a velocity vector v {\displaystyle \mathbf {v} } of magnitude v {\displaystyle v} , is given by

f ( v ) d 3 v = [ m 2 π k B T ] 3 / 2 exp ⁡ ( − m v 2 2 k B T ) d 3 v , {\displaystyle f(\mathbf {v} )~d^{3}\mathbf {v} ={\biggl [}{\frac {m}{2\pi k_{\text{B}}T}}{\biggr ]}^{{3}/{2}}\,\exp \left(-{\frac {mv^{2}}{2k_{\text{B}}T}}\right)~d^{3}\mathbf {v} ,}

where:

m is the particle mass; kB is the Boltzmann constant; T is thermodynamic temperature;

f ( v ) {\displaystyle f(\mathbf {v} )} is a probability distribution function, properly normalized so that ∫ f ( v ) d 3 v {\textstyle \int f(\mathbf {v} )\,d^{3}\mathbf {v} } over all velocities is unity.

… excerpt ends here. Continue reading the full article.

Illustrations

Maxwell–Boltzmann distribution illustration
Maxwell–Boltzmann distribution illustration
Maxwell–Boltzmann distribution: The speed probability density functions of the speeds of a few noble gases at a temperature of 298.15 K (25 °C). The y-axis is in s/m so that the area under any section of the curve (which represents the probability of the speed being in that range) is dimensionless.
The speed probability density functions of the speeds of a few noble gases at a temperature of 298.15 K (25 °C). The y-axis is in s/m so that the area under any section of the curve (which represents the probability of the speed being in that range) is dimensionless.
Maxwell–Boltzmann distribution: Simulation of a 2D gas relaxing towards a Maxwell–Boltzmann speed distribution
Simulation of a 2D gas relaxing towards a Maxwell–Boltzmann speed distribution
Maxwell–Boltzmann distribution: The Maxwell–Boltzmann distribution corresponding to the solar atmosphere. Particle masses are one proton mass, mp = 1.67×10−27 kg ≈ 1 Da, and the temperature is the effective temperature of the Sun's photosphere, T = 5800 K. 
  
    
      
        
          
            
              V
              ~
            
          
        
      
    
    {\displaystyle {\tilde {V}}}
  
, 
  
    
      
        
          
            
              V
              ¯
            
          
        
      
    
    {\displaystyle {\bar {V}}}
  
, and Vrms mark the most probable, mean, and root mean square velocities, respectively. Their values are 
  
    
      
        
          
            
              V
              ~
            
          
        
      
    
    {\displaystyle {\tilde {V}}}
  
 ≈ 9.79 km/s, 
  
    
      
        
          
            
              V
              ¯
            
          
        
      
    
    {\displaystyle {\bar {V}}}
  
 ≈ 11.05 km/s, and Vrms ≈ 12.00 km/s.
The Maxwell–Boltzmann distribution corresponding to the solar atmosphere. Particle masses are one proton mass, mp = 1.67×10−27 kg ≈ 1 Da, and the temperature is the effective temperature of the Sun's photosphere, T = 5800 K. V ~ {\displaystyle {\tilde {V}}} , V ¯ {\displaystyle {\bar {V}}} , and Vrms mark the most probable, mean, and root mean square velocities, respectively. Their values are V ~ {\displaystyle {\tilde {V}}} ≈ 9.79 km/s, V ¯ {\displaystyle {\bar {V}}} ≈ 11.05 km/s, and Vrms ≈ 12.00 km/s.

Worked examples

Example 1 — a first encounter with Maxwell–Boltzmann distribution

Start with the simplest possible case. Write down what Maxwell–Boltzmann distribution claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Maxwell–Boltzmann distribution before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Maxwell–Boltzmann distribution ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Maxwell–Boltzmann distribution

In research
Maxwell–Boltzmann distribution appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Maxwell–Boltzmann distribution in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Maxwell–Boltzmann distribution is common in secondary-school and first-year university syllabi. It links to neighbouring topics Continuous distributions, Gases, James Clerk Maxwell, so understanding it makes those chapters shorter.
In everyday life
Look for Maxwell–Boltzmann distribution outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Maxwell–Boltzmann distribution in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Maxwell–Boltzmann distribution means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Maxwell–Boltzmann distribution out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Maxwell–Boltzmann distribution in simple terms?

In physics (in particular in statistical mechanics), the Maxwell–Boltzmann distribution, or Maxwell(ian) distribution, is a particular probability distribution named after James Clerk Maxwell and Ludwig Boltzmann. It was first defined and used for describing particle speeds in idealized gases, wher…

Why does Maxwell–Boltzmann distribution matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Maxwell–Boltzmann distribution?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Maxwell–Boltzmann distribution.

Tags

  • Continuous distributions
  • Gases
  • James Clerk Maxwell
  • Ludwig Boltzmann
  • Normal distribution
  • Particle distributions

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