Entropy flow in near-critical quantum circuits
Daniel Friedan
Abstract
Near-critical quantum circuits are ideal physical systems for asymptotically large-scale quantum computers, because their low energy collective excitations evolve reversibly, effectively isolated from the environment. The design of reversible computers is constrained by the laws governing entropy flow within the computer. In near-critical quantum circuits, entropy flows as a locally conserved quantum current, obeying circuit laws analogous to the electric circuit laws. The quantum entropy current is just the energy current divided by the temperature. A quantum circuit made from a near-critical system (of conventional type) is described by a relativistic 1+1 dimensional relativistic quantum field theory on the circuit. The universal properties of the energy-momentum tensor constrain the entropy flow characteristics of the circuit components: the entropic conductivity of the quantum wires and the entropic admittance of the quantum circuit junctions. For example, near-critical quantum wires are always resistanceless inductors for entropy. A universal formula is derived for the entropic conductivity: σS(ω)=iv2S/ωT, where ωis the frequency, T the temperature, S the equilibrium entropy density and v the velocity of `light'. The thermal conductivity is Real(TσS(ω))=πv2Sδ(ω). The thermal Drude weight is, universally, v2S. This gives a way to measure the entropy density directly.
Create a lesson
Related papers
Dynamically Reentrant Skyrmion Phase in Oscillating Magnetic Fields
Z. Demir Vatansever, E. Vatansever, A. Vasilopoulos et al.
Mutual linearity in semi-Markov networks
Julian B. Voits, Ulrich S. Schwarz
Steady states in asymmetric exclusion processes with reactions: Fluctuations and non-mean field behaviour
Rohn Chatterjee, Atri Goswami, Sudip Mukherjee
Marginal Operator Deformations and Pseudocriticality in Baxter--Wu Models
Hyun-Yong Lee, Naoki Kawashima, Nikolaos G. Fytas et al.
Kardar--Parisi--Zhang density hydrodynamics in a coherent XXZ--ASEP Lindbladian
Yansheng Liu, Daoguang Li, Kaixiang Lu et al.
Brownian gyrator model with stochastic resetting
Satya N. Majumdar, Gregory Schehr, Pascal Viot et al.