12 research outputs found
Information-theoretical analysis of statistical measures for multiscale dynamics
Multiscale entropy (MSE) has been widely used to examine nonlinear systems
involving multiple time scales, such as biological and economic systems.
Conversely, Allan variance has been used to evaluate the stability of
oscillators, such as clocks and lasers, ranging from short to long time scales.
Although these two statistical measures were developed independently for
different purposes in different fields in the literature, their interest is to
examine multiscale temporal structures of physical phenomena under study. We
show that, from an information-theoretical perspective, they share some
foundations and exhibit similar tendencies. We experimentally confirmed that
similar properties of the MSE and Allan variance can be observed in
low-frequency fluctuations (LFF) in chaotic lasers and physiological heartbeat
data. Furthermore, we calculated the condition under which this consistency
between the MSE and Allan variance exists, which is related to certain
conditional probabilities. Heuristically, physical systems in nature including
the aforementioned LFF and heartbeat data mostly satisfy this condition, and
hence the MSE and Allan variance demonstrate similar properties. As a
counterexample, an artificially constructed random sequence is demonstrated,
for which the MSE and Allan variance exhibit different trends
Theory of Acceleration of Decision Making by Correlated Time Sequences
Photonic accelerators have been intensively studied to provide enhanced
information processing capability to benefit from the unique attributes of
physical processes. Recently, it has been reported that chaotically oscillating
ultrafast time series from a laser, called laser chaos, provide the ability to
solve multi-armed bandit (MAB) problems or decision-making problems at GHz
order. Furthermore, it has been confirmed that the negatively correlated
time-domain structure of laser chaos contributes to the acceleration of
decision-making. However, the underlying mechanism of why decision-making is
accelerated by correlated time series is unknown. In this study, we demonstrate
a theoretical model to account for accelerating decision-making by correlated
time sequence. We first confirm the effectiveness of the negative
autocorrelation inherent in time series for solving two-armed bandit problems
using Fourier transform surrogate methods. We propose a theoretical model that
concerns the correlated time series subjected to the decision-making system and
the internal status of the system therein in a unified manner, inspired by
correlated random walks. We demonstrate that the performance derived
analytically by the theory agrees well with the numerical simulations, which
confirms the validity of the proposed model and leads to optimal system design.
The present study paves the way for improving the effectiveness of correlated
time series for decision-making, impacting artificial intelligence and other
applications
Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk
Quantum walks (QWs) have a property that classical random walks (RWs) do not possess—the coexistence of linear spreading and localization—and this property is utilized to implement various kinds of applications. This paper proposes RW- and QW-based algorithms for multi-armed-bandit (MAB) problems. We show that, under some settings, the QW-based model realizes higher performance than the corresponding RW-based one by associating the two operations that make MAB problems difficult—exploration and exploitation—with these two behaviors of QWs
Directivity of quantum walk via its random walk replica
Quantum walks (QWs) exhibit different properties compared with classical
random walks (RWs), most notably by linear spreading and localization. In the
meantime, random walks that replicate quantum walks, which we refer to as
quantum-walk-replicating random walks (QWRWs), have been studied in the
literature where the eventual properties of QWRW coincide with those of QWs.
However, we consider that the unique attributes of QWRWs have not been fully
utilized in the former studies to obtain deeper or new insights into QWs. In
this paper, we highlight the directivity of one-dimensional discrete quantum
walks via QWRWs. By exploiting the fact that QWRW allows trajectories of
individual walkers to be considered, we first discuss the determination of
future directions of QWRWs, through which the effect of linear spreading and
localization is manifested in another way. Furthermore, the transition
probabilities of QWRWs can also be visualized and show a highly complex shape,
representing QWs in a novel way. Moreover, we discuss the first return time to
the origin between RWs and QWs, which is made possible via the notion of QWRWs.
We observe that the first return time statistics of QWs are quite different
from RWs, caused by both the linear spreading and localization properties of
QWs.Comment: 16 pages, 6 figure
Fenarimol, a Pyrimidine-Type Fungicide, Inhibits Brassinosteroid Biosynthesis
The plant steroid hormone brassinosteroids (BRs) are important signal mediators that regulate broad aspects of plant growth and development. With the discovery of brassinoazole (Brz), the first specific inhibitor of BR biosynthesis, several triazole-type BR biosynthesis inhibitors have been developed. In this article, we report that fenarimol (FM), a pyrimidine-type fungicide, exhibits potent inhibitory activity against BR biosynthesis. FM induces dwarfism and the open cotyledon phenotype of Arabidopsis seedlings in the dark. The IC50 value for FM to inhibit stem elongation of Arabidopsis seedlings grown in the dark was approximately 1.8 ± 0.2 μM. FM-induced dwarfism of Arabidopsis seedlings could be restored by brassinolide (BL) but not by gibberellin (GA). Assessment of the target site of FM in BR biosynthesis by feeding BR biosynthesis intermediates indicated that FM interferes with the side chain hydroxylation of BR biosynthesis from campestanol to teasterone. Determination of the binding affinity of FM to purified recombinant CYP90D1 indicated that FM induced a typical type II binding spectrum with a Kd value of approximately 0.79 μM. Quantitative real-time PCR analysis of the expression level of the BR responsive gene in Arabidopsis seedlings indicated that FM induces the BR deficiency in Arabidopsis
Asymmetric quantum decision-making
Abstract Collective decision-making plays a crucial role in information and communication systems. However, decision conflicts among agents often impede the maximization of potential utilities within the system. Quantum processes have shown promise in achieving conflict-free joint decisions between two agents through the entanglement of photons or the quantum interference of orbital angular momentum (OAM). Nonetheless, previous studies have shown symmetric resultant joint decisions, which, while preserving equality, fail to address disparities. In light of global challenges such as ethics and equity, it is imperative for decision-making systems to not only maintain existing equality but also address and resolve disparities. In this study, we investigate asymmetric collective decision-making theoretically and numerically using quantum interference of photons carrying OAM or entangled photons. We successfully demonstrate the realization of asymmetry; however, it should be noted that a certain degree of photon loss is inevitable in the proposed models. We also provide an analytical formulation for determining the available range of asymmetry and describe a method for obtaining the desired degree of asymmetry
Effective generation mechanisms of tropical instability waves as represented by high-resolution coupled atmosphere–ocean prediction experiments
Abstract Cusp-shaped fluctuations of the sea surface temperature (SST) front in the tropical Pacific, now known as tropical instability waves (TIWs), were discovered by remote sensing in the 1970s. Their discovery was followed by both theoretical and analytical studies, which, along with in situ observations, identified several possible generation mechanisms. Although modeling studies have shown that TIWs strongly influence the heat budget, their influence on local variations of realistically initialized predictions is not yet understood. We here evaluate a series of medium-range (up to ~ 10 days) coupled atmosphere–ocean predictions by a coupled model with different horizontal resolutions. Observational SST, surface wind stress, heat flux, and pressure data showed that representation of temporally and spatially local variations was improved by resolving fine-scale SST variations around the initialized coarse-scale SST front fluctuations of TIWs. Our study thus demonstrates the advantage of using high-resolution coupled models for medium-range predictions. In addition, analysis of TIW energetics showed two dominant sources of energy to anticyclonic eddies: barotropic instability between equatorial zonal currents and baroclinic instability due to intense density fronts. In turn, the eddy circulation strengthened both instabilities in the resolved simulations. This revealed feedback process refines our understanding of the generation mechanisms of TIWs