Statistical mechanics, structure of matter Definition
Parallel tempering
Builds on Markov chain Monte CarloBoltzmann distributionDetailed balanceMetropolis–Hastings algorithm
Definition
Let be a finite set of configurations with energy , and let be the Boltzmann distribution at inverse temperature . Fix inverse temperatures . Parallel tempering is the Markov chain on , with states , whose steps are of two kinds.
- Local moves: for each , update by a Markov chain that leaves invariant.
- Swap moves: choose and propose to exchange and ; accept the exchange with probability
Remarks
Both kinds of moves leave the product measure invariant. For the swap, the ratio of the product weights after and before is as follows. so the rule of clause 2 is the Metropolis rule for a symmetric proposal, and it satisfies detailed balance. Hence the marginal of is , and averages of estimate thermal averages at the lowest temperature. Example: let the hotter copy have the lower energy. Then and , so the exponent is positive and the swap is always accepted. In this way low-energy states move towards the cold end. Non-example: accepting every swap would break the invariance, because a high-energy state from the hot copy would be pushed into the cold copy too often. The temperatures must be close enough that the energy distributions of neighbouring copies overlap; otherwise almost all swaps are rejected.
Reading path
To understand this page from the ground up, read these 5 pages in order. The foundations come first.
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- no evidence level
- Boltzmann distribution concept
- Detailed balance concept
- Markov chain Monte Carlo concept
- Metropolis–Hastings algorithm concept
- Parallel tempering definition
Further reading
About this page
| Tag | HB7J6SYG00 |
|---|---|
| URI | m2://HB7J6SYG00 |
| Kind | definition |
| Writing | W0 stub |
| MSC | 82M31, 65C05, 65C40 |
| Defines | Parallel tempering |
| Uses | Markov chain Monte Carlo, Boltzmann distribution, Detailed balance, Metropolis–Hastings algorithm |
| Changed | 3 November 2026 |
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