Do we need Lindblad operators to describe spontaneous emission

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SUMMARY

The discussion centers on the necessity of Lindblad operators for describing spontaneous emission in quantum systems, particularly in the context of quantum optics. While Griffith and Sakurai's Quantum Mechanics book treats spontaneous emission as a closed system using time-dependent perturbation theory, the master equation approach in quantum optics necessitates Lindblad operators for open systems. The Lindblad equation, which governs the evolution of the reduced density matrix, is established as the most general differential equation for Markovian evolution, distinguishing between stochastic processes and deterministic probability functions.

PREREQUISITES
  • Understanding of density matrices and their evolution
  • Familiarity with the Lindblad equation and its applications
  • Knowledge of Markovian processes in quantum mechanics
  • Basic principles of quantum optics and spontaneous emission
NEXT STEPS
  • Study the derivation and applications of the Lindblad equation in quantum mechanics
  • Explore the concept of reduced density matrices and their significance in open quantum systems
  • Investigate the differences between stochastic processes and deterministic probability functions
  • Learn about time-dependent perturbation theory as presented in Griffith and Sakurai's Quantum Mechanics
USEFUL FOR

Quantum physicists, researchers in quantum optics, and students studying open quantum systems will benefit from this discussion, particularly those interested in the mathematical foundations of spontaneous emission and Markovian dynamics.

td21
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In Griffith and Sakurai QM book, spontaneous emission is treated as a closed system subject to time-dependent perturbation.

Yet in quantum optics sponantanoues emission is treated as in the form master equation of density matrix. Even in two levels system where there is only one spontaneous emission rate, master equation is formulated to described sponantanoues emission. Why do we need Lindblad operators for two level system?
 
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A closed quantum system as a whole has a unitary evolution. But sometimes you need to describe the evolution of an open system where you have no access to the degrees of freedom(dof) that the system is interacting with. In those cases you need a quantity that describes the evolution of the dof of the system but not the environment. This can't be done using wave-functions. So you form the density matrix of the system+environment and then trace-out the environmental dof. The resulting quantity is called the reduced density matrix of the system and its evolution is non-unitary and non-deterministic. Such an evolution is an stochastic process and should be described by an stochastic differential equation. Now considering the Heisenberg equation of motion and some simplifying assumptions, you get the Lindblad equation.
 
ShayanJ said:
The resulting quantity is called the reduced density matrix of the system and its evolution is non-unitary and non-deterministic. Such an evolution is an stochastic process and should be described by an stochastic differential equation. Now considering the Heisenberg equation of motion and some simplifying assumptions, you get the Lindblad equation.
You are right that Lindblad equation is non-unitary, but it is deterministic and not stochastic.
 
Demystifier said:
You are right that Lindblad equation is non-unitary, but it is deterministic and not stochastic.
But Lindblad equation is the most general differential equation for a Markovian evolution. Being Markovian is a property of stochastic processes!
 
ShayanJ said:
But Lindblad equation is the most general differential equation for a Markovian evolution. Being Markovian is a property of stochastic processes!
One should distinguish Markov process from Markov probability. Markov process is indeed a stochastic process, but such a process is determined by a probability which can have a deterministic dependence on time. For instance, the standard 1-dimensional random walk is a stochastic process with a constant probability (at each step, the probability is always 1/2 for any of the two directions). The Lindblad equation describes only the probability function (more technically, the probability density matrix), not the stochastic process.
 
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