Statistical Physics: Solving Exam Questions and Using External Resources

In summary, the conversation discusses various topics related to physics, including calculating heat needed to increase microstates, probability calculations for weather forecasts, maximizing work output in a heat machine, heat capacity in an ideal gas and its relation to Fermi gases, and calculating entropy at different temperatures.
  • #1
murat386
3
0
Almost no one has answered.To take some external help, i write all questions here, maybe someone have an answer.

1)An aluminium cube cooled down to 90 Kelvin.At this point there is too many microstates available.how much heat we need, to increase these microstates in factor of 10[tex]^{10}[/tex] ? Answer in Joule unit.

2)In a simple October's forecast, days are tagged as rainy or shiny. Probability of a shiny day followed a shiny day is 0.8 .Probability of a rainy day followed by shiny air is 0.4 .Probability of 1st October to be shiny is 0.75
a)Find probability of 2nd and 3rd October be shiny.
b) If 1st October is shiny, what's probability is 3rd October to be rainy?

3)Two heat tanks, with constant volume and heat capacity, are used to power up a heat machine.Their startup temperature is T[tex]_{a}[/tex] and T[tex]_{b}[/tex].Assume that this heat machine gives as most possible product.(Net entropy change is zero).What is highest work that can be obtained from this machine?

4) A solid, has N count, 1/2 spinned atoms.In a enough temperature, these spins rotated randomly.But enough low temperatures, they are acted ferromagnetically.Due this reason, all spins are rotated same in T->0 K .In a rough given formula spin oriented addition to heat capacity is C(T)

C(T) = C[tex]_{1}[/tex] = ([tex]\frac{2T}{T_{1}}[/tex] - 1 ) if T[tex]_{1/2}[/tex] < T < T[tex]_{1}[/tex]
( 1 and 1/2 are subscripts. Sown wrongly)
0 else

So take maximum probable of C[tex]_{1}[/tex] using entropy. (C subscript 1)

5) In a fermi gase,related to [tex]\epsilon[/tex][tex]_{f}[/tex] , state density D([tex]\epsilon[/tex][tex]_{f}[/tex]) , show that heat capacity is written as

C[tex]_{v}[/tex] = [tex]\frac{\pi^{2}}{3}[/tex] D([tex]\epsilon[/tex][tex]_{f}[/tex]) k[tex]^{2}[/tex] T
 
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  • #2
6) An ideal gas has C_{v} = 3/2 k.If it is heated up to T, it's entropy will be S(T) .Calculate entropy in a lower temperature T_{1}, using this equation.
 
  • #3


1) To increase the microstates by a factor of 10^10, we need to add an amount of heat equal to 10^10 times the initial heat content of the system. This can be calculated using the formula for the heat capacity of a solid, C = γNk, where γ is the specific heat capacity, N is the number of atoms, and k is the Boltzmann constant. Thus, the heat needed is 10^10γNk.

2) a) The probability of 2nd October being shiny is 0.8, as it follows a shiny day. The probability of 3rd October being shiny is 0.8*0.8 = 0.64, as it follows two consecutive shiny days.
b) If 1st October is shiny, the probability of 3rd October being rainy is 0.4, as it follows a shiny day and then a rainy day.

3) The highest work that can be obtained from the heat machine is given by the Carnot efficiency, which is equal to 1-Tb/Ta. This can be calculated using the formula for the efficiency of a heat engine, η = (T1-T2)/T1, where T1 is the hot reservoir temperature and T2 is the cold reservoir temperature.

4) The maximum probable value of C1 can be determined by maximizing the entropy of the system, which is given by S = k ln(Ω), where Ω is the number of microstates available to the system. In this case, Ω is equal to 2^N, as each spin can have two possible orientations. Thus, the maximum probable value of C1 is when all spins are aligned, which occurs at T = 0 K. Therefore, C1 = Nk.

5) The heat capacity of a fermi gas can be calculated using the formula C = γNk, where γ is the specific heat capacity, N is the number of particles, and k is the Boltzmann constant. In this case, the number of particles is given by the state density, N = D(εf)V, where V is the volume and D(εf) is the state density at the fermi energy. Thus, the heat capacity can be written as C = γD(εf)Vk. Using the relation between the fermi energy and temperature, εf = π^2kT
 

Related to Statistical Physics: Solving Exam Questions and Using External Resources

1. What is statistical physics?

Statistical physics is a branch of physics that uses statistical methods, probability theory, and mathematical models to study the properties and behavior of large systems of particles. It is used to explain and predict macroscopic phenomena such as temperature, pressure, and entropy, based on the microscopic behavior of individual particles.

2. What topics are typically covered in a statistical physics exam?

A statistical physics exam usually covers topics such as thermodynamics, kinetic theory, statistical mechanics, and quantum statistics. It may also include applications of these concepts to real-world systems, such as gases, liquids, and solids.

3. How should I prepare for a statistical physics exam?

To prepare for a statistical physics exam, it is important to review the fundamental concepts and equations, as well as practice solving problems and applying the concepts to different scenarios. It can also be helpful to attend review sessions or study groups, and to consult with your professor or classmates for clarification on any confusing topics.

4. What are some common misconceptions about statistical physics?

One common misconception about statistical physics is that it is only applicable to idealized systems and cannot be used to describe real-world phenomena. However, statistical physics is a powerful tool that can be applied to a wide range of systems, including complex and non-ideal systems. Another misconception is that statistical physics is solely based on probability and does not involve any physical laws or principles. In reality, statistical physics is built upon fundamental laws of thermodynamics and classical mechanics.

5. What skills are important for success in a statistical physics exam?

In addition to a solid understanding of the fundamental concepts, success in a statistical physics exam also requires strong problem-solving skills, the ability to apply theoretical concepts to practical situations, and the ability to interpret and analyze data. It is also important to have a good grasp of mathematical techniques and equations used in statistical physics, such as probability, differential equations, and statistical distributions.

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