Quantum speed limits in arbitrary phase spaces
Weiquan Meng1and Zhenyu Xu1
1School of Physical Science and Technology, Soochow University, Suzhou 215006, China
(Dated: August 25, 2023)
Quantum speed limits (QSLs) provide an upper bound for the speed of evolution of quantum states
in any physical process. Based on the Stratonovich-Weyl correspondence, we derive a universal QSL
bound in arbitrary phase spaces that is applicable for both continuous variable systems and finite-
dimensional discrete quantum systems. This QSL bound allows the determination of speed limit
bounds in specific phase spaces that are tighter than those in Wigner phase space or Hilbert space
under the same metric, as illustrated by several typical examples, e.g., a single-mode free field and N-
level quantum systems in phase spaces. This QSL bound also provides an experimentally realizable
way to examine the speed limit in phase spaces relevant to applications in quantum information and
quantum optics.
I. INTRODUCTION
Quantum speed limits (QSLs) set the upper bound
on the speed for quantum systems evolving in an arbi-
trary physical process [1–3]. The milestone of describing
the QSL time as the intrinsic time scale of quantum dy-
namics was achieved by Mandelstam and Tamm, who
clarified the longstanding debate on the explanations for
the time-energy uncertainty relationship [4]. The energy
fluctuation restricts the minimum time for a quantum
state to evolve into its orthogonal state. Apart from the
standard deviation of the energy [4–6], alternative QSL
time bounds based on the averaged energy [7–10] and
the interplay among them [11–13] have been developed
in succession. In the last decade, QSLs have even been
extended to the fields of open systems involving various
metrics [14–20], quantum dynamical speedup [16,21–26],
information geometry [27], time-optimal quantum con-
trol [28–32], quantum and macroscopic stochastic pro-
cesses [33–35], non-Hermitian systems [15,36–38], dy-
namics of many-body quantum systems [39,40], the evo-
lution of observables [41–43], and recently the topological
structure of the dynamics [44]. Indeed, the QSL rep-
resents a powerful tool for evaluating the performance
of quantum computers [45], the accuracy of quantum
metrology [46,47], and the efficiency in quantum thermo-
dynamics [48–56], among others. Thus, extensive effort
has been applied toward experimental verification to this
end [57–61].
Apart from the well-known Schr¨odinger’s wave func-
tion, Heisenberg’s matrix mechanics, and Feynman’s
path integral, the phase-space formalism of quantum me-
chanics has an advantage in terms of its resemblance to
classical statistical mechanics and supports a profound
understanding of the underlying statistical properties
[62]. The pioneering work regarding the study of QSLs in
phase spaces was presented by Deffner, who found that
the QSL in the Wigner (W) phase space is equivalent
to that in the density operator space and much easier to
perform computations involving continuous variable sys-
tems [63]. Later, because the Wphase space retains the
structure of the classical phase space through quantum-
classical correspondence, Shanahan et al. discovered that
the QSL is not a particular quantum phenomenon but a
universal property of the time evolution of continuous
variable systems in the Wphase space [64]. Meantime,
questions regarding the speed limit in the Wphase space
have led to the intensive study of the classical speed limit
over the past few years [64–67].
For continuous variable systems, the Wfunction is the
most widely used phase-space quasiprobability represen-
tation with symmetric ordering of the position and mo-
mentum operators (or equivalently aand a†) [68]. Nev-
ertheless, it is not unique, and a large number of well-
known phase-space quasiprobability distribution func-
tions exist [62]. For instance, the Glauber-Sudarshan P
function [69,70] with a normal ordering of aand a†can
be used to diagonalize the density operator in terms of
coherent states and is fundamental in photoelectric detec-
tion [71]. Additionally, the Husimi Qfunction [72] with
the antinormal ordering of aand a†provides a possible
way to define a nonnegative quasiprobability distribu-
tion, and the Cahill-Glauber s-parametrized quasiprob-
ability distributions incorporate the above W,P, and Q
functions, with s= 0,1, and −1, respectively [73,74].
In addition, the flourishing development in quantum
information and quantum technology now requires the
consideration of finite-dimensional systems, e.g., an en-
semble of spins, to define corresponding quasiprobability
distribution functions (see a recent review [75]). Com-
monly, there are two methods. The first method involves
generating discrete analogues of the quasiprobability dis-
tribution functions [76–78], an approach that has been
used in various applications in quantum-state tomogra-
phy [79], resource theory for quantum computation [80–
82], and studies of the dynamics of many-body quantum
systems [83,84]. The second method involves employ-
ing generalized coherent states [85–90] to provide insights
into the study of quantum foundations, e.g., the recent
construction of a general statistical framework for finite-
dimensional discrete quantum systems [91] and the inter-
pretation of quantum entanglement with classical trajec-
tories [92].
At this point, the following two questions naturally
arXiv:2210.14278v2 [quant-ph] 24 Aug 2023