Speaker
Description
First-order phase transitions characterized by the coexistence of phases are commonly observed in the surrounding world, e.g. in the freezing of water. Continuous – second-order – phase transitions also exist in classical physics, e.g. the transition between ferro- and paramagnetism at the Curie temperature. Whereas the latter class has seen straightforward generalizations to quantum systems for decades, the notion of a first-order quantum phase transition remains to be elucidated.
Bistability in certain small quantum systems has been identified as signature of first order quantum phase transitions, however, this identification is problematic: a randomly switching telegraph signal between two well-resolved attractors can also be observed in quantum dynamics distinct from phase transitions. For example, the famous electron-shelving scheme – used in atomic clocks or for qubit measurement in ion-trap quantum computers – produces a similar signal without any connection to phase transitions.
There is a missing element to support the interpretation of bistability as a first-order quantum phase transition: it must be shown that bistability is only a finite-size effect, and there exists an idealized thermodynamic limit, where temporal bistability is replaced by hysteresis. This idealized thermodynamic limit can be introduced such that the physical system remains a small quantum system with a few degrees of freedom, that is, the passage to the thermodynamic limit does not involve a quantum-to-classical transition. In this talk, I present a prototype of this procedure by constructing a finite-size scaling [1] for the recently-observed photon-blockade-breakdown effect [2,3] to justify its classification as a first-order dissipative quantum phase transition.
The work involves heavy numerics, performed on a virtual cluster defined within the Wigner Cloud. The applied software, as always in my work, was C++QED: a versatile open-source C++/Python application-programming framework for simulating open quantum dynamics [4-7], developed by our group. The framework uses an adaptive-timestep version of the Monte Carlo wave-function method [8], which can be readily paralellized. In the talk, I will also sketch the computer-physics aspects of the work.
[1] Vukics A, Dombi A, Fink J M and Domokos P 2019 Quantum 3 150 URL
https://doi.org/10.22331/q-2019-06-03-150
[2] Fink J M, Dombi A, Vukics A, Wallraff A and Domokos P 2017 Phys.
Rev. X 7(1) 011012 URL https://doi.org/10.1103/PhysRevX.7.011012.
[3] Carmichael H J 2015 Phys. Rev. X 5(3) 031028 URL
https://doi.org/10.1103/PhysRevX.5.031028.
[4] http://cppqed.sf.net
[5] Vukics A and Ritsch H 2007 Eur. Phys. J. D 44 585–599
[6] Vukics A 2012 Comp. Phys. Comm. 183 1381–1396
[7] Sandner R and Vukics A 2014 Comp. Phys. Comm. 185 2380–2382
[8] Kornyik M and Vukics A 2019 Comp. Phys. Comm. 238 88–101
