884 research outputs found
Quantum information and statistical mechanics: an introduction to frontier
This is a short review on an interdisciplinary field of quantum information
science and statistical mechanics. We first give a pedagogical introduction to
the stabilizer formalism, which is an efficient way to describe an important
class of quantum states, the so-called stabilizer states, and quantum
operations on them. Furthermore, graph states, which are a class of stabilizer
states associated with graphs, and their applications for measurement-based
quantum computation are also mentioned. Based on the stabilizer formalism, we
review two interdisciplinary topics. One is the relation between quantum error
correction codes and spin glass models, which allows us to analyze the
performances of quantum error correction codes by using the knowledge about
phases in statistical models. The other is the relation between the stabilizer
formalism and partition functions of classical spin models, which provides new
quantum and classical algorithms to evaluate partition functions of classical
spin models.Comment: 15pages, 4 figures, to appear in Proceedings of 4th YSM-SPIP (Sendai,
14-16 December 2012
Dynamic mode decomposition in vector-valued reproducing kernel Hilbert spaces for extracting dynamical structure among observables
Understanding nonlinear dynamical systems (NLDSs) is challenging in a variety
of engineering and scientific fields. Dynamic mode decomposition (DMD), which
is a numerical algorithm for the spectral analysis of Koopman operators, has
been attracting attention as a way of obtaining global modal descriptions of
NLDSs without requiring explicit prior knowledge. However, since existing DMD
algorithms are in principle formulated based on the concatenation of scalar
observables, it is not directly applicable to data with dependent structures
among observables, which take, for example, the form of a sequence of graphs.
In this paper, we formulate Koopman spectral analysis for NLDSs with structures
among observables and propose an estimation algorithm for this problem. This
method can extract and visualize the underlying low-dimensional global dynamics
of NLDSs with structures among observables from data, which can be useful in
understanding the underlying dynamics of such NLDSs. To this end, we first
formulate the problem of estimating spectra of the Koopman operator defined in
vector-valued reproducing kernel Hilbert spaces, and then develop an estimation
procedure for this problem by reformulating tensor-based DMD. As a special case
of our method, we propose the method named as Graph DMD, which is a numerical
algorithm for Koopman spectral analysis of graph dynamical systems, using a
sequence of adjacency matrices. We investigate the empirical performance of our
method by using synthetic and real-world data.Comment: 34 pages with 4 figures, Published in Neural Networks, 201
Cluster-based architecture for fault-tolerant quantum computation
We present a detailed description of an architecture for fault-tolerant
quantum computation, which is based on the cluster model of encoded qubits. In
this cluster-based architecture, concatenated computation is implemented in a
quite different way from the usual circuit-based architecture where physical
gates are recursively replaced by logical gates with error-correction gadgets.
Instead, some relevant cluster states, say fundamental clusters, are
recursively constructed through verification and postselection in advance for
the higher-level one-way computation, which namely provides error-precorrection
of gate operations. A suitable code such as the Steane seven-qubit code is
adopted for transversal operations. This concatenated construction of verified
fundamental clusters has a simple transversal structure of logical errors, and
achieves a high noise threshold ~ 3 % for computation by using appropriate
verification procedures. Since the postselection is localized within each
fundamental cluster with the help of deterministic bare controlled-Z gates
without verification, divergence of resources is restrained, which reconciles
postselection with scalability.Comment: 16 pages, 34 figure
Anti-Zeno Effect for Quantum Transport in Disordered Systems
We demonstrate that repeated measurements in disordered systems can induce
quantum anti-Zeno effect under certain condition to enhance quantum transport.
The enhancement of energy transfer is really exhibited with a simple model
under repeated measurements. The optimal measurement interval for the anti-Zeno
effect and the maximal efficiency of energy transfer are specified in terms of
the relevant physical parameters. Since the environment acts as frequent
measurements on the system, the decoherence-induced energy transfer, which has
been discussed recently for photosynthetic complexes, may be interpreted in
terms of the anti-Zeno effect. We further find an interesting phenomenon, where
local decoherence or repeated measurements may even promote entanglement
generation between the non-local sites.Comment: 5pages, 3 figures; v2: published versio
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