The attempt to gain a theoretical understanding of the concept of time in quantum mechanics has triggered significant progress towards the search for faster and more efficient quantum technologies. One of such advances consists in the interpretation of the time-energy uncertainty relations as lower bounds for the minimal evolution time between two distinguishable states of a quantum system, also known as quantum speed limits. Here we discuss how the nonuniqueness of a bona fide measure of distinguishability defined on the quantum-state space affects the quantum speed limits and can be exploited in order to derive improved bounds. Specifically, we establish an infinite family of quantum speed limits valid for unitary and nonunitary evolutions, based on an elegant information geometric formalism. Some possible applications in quantum thermodynamics are also discussed.
The canonical quantization of gravity leads to the Hamiltonian constraint, that is, physical states of the theory are annihilated by the Hamiltonian. Combined with the Schrodinger equation, the Hamiltonian constraint dictates that the physical states do not evolve in time. This poses a problem for time in the theory: Given that the physical states do not evolve, how do we explain the time evolution we see around us?I will begin by reviewing how the Hamiltonian constraint arises in both classical and quantum mechanics and then introduce the conditional probability interpretation of time, which is a possible answer to the question above. I will then discuss two generalizations of this interpretation which are necessary if it is to be applied to time in quantum gravity.
Simultaneous estimation of multiple parameters in quantum metrological models is complicated by factors relating to the (i) existence of a single probe state allowing for optimal sensitivity for all parameters of interest, (ii) existence of a single measurement optimally extracting information from the probe state on all the parameters, and (iii) statistical independence of the estimated parameters. We consider the situation when these concerns present no obstacle and for every estimated parameter the variance obtained in the multiparameter scheme is equal to that of an optimal scheme for that parameter alone, assuming all other parameters are perfectly known. We call such models compatible. In establishing a rigorous framework for investigating compatibility, we clarify some ambiguities and inconsistencies present in the literature and discuss several examples to highlight interesting features of unitary and non-unitary parameter estimation, as well as deriving new bounds for physical problems of interest, such as the simultaneous estimation of phase and local dephasing.