Must ensembles be homogeneous?

In summary, an ensemble is a collection of systems prepared in the same way. This can include systems in the same pure state or in different pure states with a statistical mixture. However, a proper mixture must have pure states as its eigenstates and an improper mixture is prepared through ignorance of a measurement outcome. Nonlocal measurements can distinguish between proper and improper mixtures. Decoherence can also lead to improper mixtures. Proper mixtures can be created by randomly mixing up pure ensembles. As long as the relative weights of the pure states add up to 1, any proper mixture can represent a mixed state.
  • #1
normvcr
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An ensemble is a collection of systems, all prepared in the same way. Does this mean that all the systems are in the same state? I have seen some authors create ensembles where 30% of the systems are in a state, s, and 70% of the systems are in a state, t . As far as measurements go, this ensemble represents the mixed state 0.3 s + 0.7 t . Is this accepted as a valid ensemble for this mixed state?
 
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  • #2
Yes, the same pure state per individual system. It's one of the underlying (i.e. not explicit) assumptions in QM: the ability to prepare a system in a certain state.
 
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What about the mixed (non-pure) state example that is in the original post?
 
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I honestly don't know how to physically prepare a statistical mixture. A pure one can be done through a Stern-Gerlach type of experimental setup. So, sorry for not helping more, I'm rather into the mathematical delopments of QM than to the their connection with real-life experiments.
 
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Thanks for the info. Perhaps, someone else will know about ensembles of mixed states.
 
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Yes, the ensemble can be mixed - it can be any ensemble that is represented by a density matrix. One way to prepare a mixed state is to perform a measurement, but don't sort according to the outcome. The ensemble will be a statistical mixture of all possible measurement outcomes. The mixed density matrix prepared by ignorance of a measurement outcome is called a "proper mixture".

A mixed state can also be prepared by preparing a system that is in a pure state. If the subsystems are entangled, then the reduced density matrix of a subsystem will be mixed. As an example of a mixed state preparation, take a Bell state of a pair of spins. The Bell state is a pure state. If you make observations on only one spin in the entangled pair, the reduced density matrix describing the state of that spin is mixed. The mixed density matrix prepared by ignorance of some degrees of freedom in a total pure state is called an "improper mixture".

There is a relationship between the two ways of preparing a mixed state. Take the Bell state again. If we always measure on spin A first, we will cause the wave function to collapse. However, the person measuring spin B, if performing his measurement locally and not sorting according to the outcome of the measurement on spin A, will basically be doing a measurement on a mixed state prepared by measurement followed by not sorting. This is an example of local measurements being completely unable to distinguish between proper and improper mixtures. Nonlocal measurements can distinguish between them.
 
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Thank you for the detailed response. From the question in the original post, the mixed state 0.3 s + 0.7 t is represented by the ensemble having 30% of the systems in state s and 70% of the systems in state t, but this is not a proper mixture unless the states s and t happen to be the two eigen states of a measurement operator, with eigenvalues 0.3 and 0.7, respectively. Do you see any problem with using this ensemble, which is neither proper nor improper, to represent the mixed state?
 
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normvcr said:
Thank you for the detailed response. From the question in the original post, the mixed state 0.3 s + 0.7 t is represented by the ensemble having 30% of the systems in state s and 70% of the systems in state t, but this is not a proper mixture unless the states s and t happen to be the two eigen states of a measurement operator, with eigenvalues 0.3 and 0.7, respectively. Do you see any problem with using this ensemble, which is neither proper nor improper, to represent the mixed state?

You understand about proper and improper mixtures :D:D:D:D:D:D:D.

Improper ones happen all the time due to decoherence.

Proper ones are easily done simply by randomly mixing up pure ensembles. Say for axample you want 1/6th in a certain pure state and 5/6th in another pure state simply take a dice, throw it, and every time you get a 1 select it from one state otherwise from another. Do that a large number of times.

I will leave you to think about the implications of the fact it can conceptually be made as large as you like, but not infinite. Its the same issue you get in stochastic models used in applied math all the time.

Thanks
Bill
 
  • #9
normvcr said:
Thank you for the detailed response. From the question in the original post, the mixed state 0.3 s + 0.7 t is represented by the ensemble having 30% of the systems in state s and 70% of the systems in state t, but this is not a proper mixture unless the states s and t happen to be the two eigen states of a measurement operator, with eigenvalues 0.3 and 0.7, respectively. Do you see any problem with using this ensemble, which is neither proper nor improper, to represent the mixed state?

The state you describe is a proper mixture for any s and t that are pure states. A proper mixture is just a statistically weighted mixture of any pure states, so as long as the relative weights add up to 1, it's ok. http://en.wikipedia.org/wiki/Density_matrix
 

Related to Must ensembles be homogeneous?

What does it mean for ensembles to be homogeneous?

Homogeneous ensembles are those that have similar or identical characteristics, such as composition, behavior, or properties. In other words, the individual elements of the ensemble are consistent with each other.

Why is homogeneity important in ensembles?

Homogeneity allows for better control and understanding of the ensemble as a whole. It also ensures that any observations or experiments performed on the ensemble are reflective of the entire group and not just a subset of it.

Can an ensemble be heterogeneous?

Yes, an ensemble can be heterogeneous, meaning its elements have different characteristics. However, heterogeneous ensembles may be more difficult to study and may lead to less reliable results compared to homogeneous ensembles.

How can homogeneity be achieved in ensembles?

Homogeneity can be achieved by controlling the factors that contribute to the characteristics of the ensemble, such as the composition, environment, and interactions between the elements. This can be done through careful selection and preparation of the ensemble elements.

Are there any downsides to having a homogeneous ensemble?

In some cases, a homogeneous ensemble may not accurately reflect the real-world conditions or variations. This can limit the generalizability of results and may require further study with heterogeneous ensembles to validate findings.

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