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A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that what is usually computed in physicssuch a solution (lowest action configuration i.e. max-likelihood, as is usually computed in physics) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless anyways, so splitting hairs regarding the terminology here is quite pointless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuations at different points (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, it is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc. The essence of all those conditions comes down the whether the effect of fluctuations is sufficiently controlled/negligible. A common theme in statistical physics is the applicability of these approximations in one parameter regime, and the dominance of fluctuations in another regime, with a phase transition as the appropriate description changes from one renormalization group basin of attraction to another.

A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless anyways, so splitting hairs regarding the terminology here is quite pointless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuations at different points (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, it is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that such a solution (lowest action configuration i.e. max-likelihood, as is usually computed in physics) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless anyways, so splitting hairs regarding the terminology here is quite pointless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuations at different points (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, it is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc. The essence of all those conditions comes down the whether the effect of fluctuations is sufficiently controlled/negligible. A common theme in statistical physics is the applicability of these approximations in one parameter regime, and the dominance of fluctuations in another regime, with a phase transition as the appropriate description changes from one renormalization group basin of attraction to another.

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A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless anyways, so splitting hairs regarding the terminology here is quite pointless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuation degrees of freedomfluctuations at different points (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, thisit is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuation degrees of freedom (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, this is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless anyways, so splitting hairs regarding the terminology here is quite pointless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuations at different points (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, it is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

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A quantum field theory is modeled by a probability distribution (measure) distribution over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by charcaterizingcharacterizing their distributions byusing moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical “field profile”"field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may computeconveniently solve for self consistent-consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuation degrees of freedom (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, this is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

A quantum field theory is modeled by a probability (measure) distribution over the space of all field configurations, specified implicitly by an action. We seek to describe systems by charcaterizing their distributions by moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation neglects all "fluctuations" in field values at each point and considers a classical “field profile”. Commonly, this field profile is also assumed to be uniform in space, so that one may compute self consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure.

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuation degrees of freedom (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, this is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

A quantum field theory is modeled by a probability distribution (measure) over the space of all field configurations, specified implicitly by an action functional. We seek to describe systems by characterizing their distributions using moments (correlation functions).

A simple characterization for the multi-variate distribution (each point corresponds to one random variable) is to specify it's mean at every point in space. The mean field approximation does exactly that -- it neglects all "fluctuations" in field values at each point and considers a classical "field profile". Commonly, this field profile is also assumed to be uniform in space, so that one may conveniently solve for self-consistent answers for the background field value. Also, note that what is usually computed in physics (lowest action configuration i.e. max-likelihood) is actually the "mode" of the distribution -- but the mode and the mean are interchangeable if the distribution is peaked and large fluctuations have negligible measure. (Note: If the system is not in that regime, then these approximations/truncations are useless)

Quantum mechanically, the true solution is the superposition of a bunch of configurations which are modeled as "fluctuations" around the "mean" field. Neglecting any interactions between these fluctuation degrees of freedom (suppressed by a coupling constant) the leading order dynamics is captured by a quadratic Lagrangian — just the kinetic/gradient terms for the fluctuations. As this action leads to a Gaussian measure on the fluctuating degrees of freedom, this is also referred to as the Gaussian approximation. This is equivalent to treating each fluctuation degree of freedom as an independent harmonic oscillator (essentially "free" field theory).

Whether each of these approximations is useful depends on details like the size of the coupling constant, dimensionality of the system, etc.

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