Regression Study of Odorant Chemical Space, Molecular Structural Diversity, and Natural Language Description.

Odor is analyzed on the human olfactometry systems in various steps. The mapping from chemical structures to olfactory perceptions of smell is an extremely challenging task. Scientists have been unable to find a measure to distinguish the perceptual similarity between odorants. In this study, we report regression analysis and visualization based on the odorant chemical space. We discuss the relation between the odor descriptors and their structural diversity for odorants groups associated with each odor descriptor. We studied the influence of structural diversity on the odor descriptor predictability. The results suggest that the diversity of molecular structures, which is associated with the same odor descriptor, is related to the resolutional confusion with the odor descriptor.

Order recognition by Schubert polynomials generated by optical near-field statistics via nanometre-scale photochromism.

Irregular spatial distribution of photon transmission through a photochromic crystal photoisomerized by a local optical near-field excitation was previously reported, which manifested complex branching processes via the interplay of material deformation and near-field photon transfer therein. Furthermore, by combining such naturally constructed complex photon transmission with a simple photon detection protocol, Schubert polynomials, the foundation of versatile permutation operations in mathematics, have been generated. In this study, we demonstrated an order recognition algorithm inspired by Schubert calculus using optical near-field statistics via nanometre-scale photochromism. More specifically, by utilizing Schubert polynomials generated via optical near-field patterns, we showed that the order of slot machines with initially unknown reward probability was successfully recognized. We emphasized that, unlike conventional algorithms, the proposed principle does not estimate the reward probabilities but exploits the inversion relations contained in the Schubert polynomials. To quantitatively evaluate the impact of Schubert polynomials generated from an optical near-field pattern, order recognition performances were compared with uniformly distributed and spatially strongly skewed probability distributions, where the optical near-field pattern outperformed the others. We found that the number of singularities contained in Schubert polynomials and that of the given problem or considered environment exhibited a clear correspondence, indicating that superior order recognition is attained when the singularity of the given situations is presupposed. This study paves way for physical computing through the interplay of complex natural processes and mathematical insights gained by Schubert calculus.

Scanning near-field optical spectroscopy and carrier transport based analysis in mesoscopic regions for two-dimensional semiconductors.

The measurements of photoexcited transport in mesoscopic regimes reveal the states and properties of mesoscopic systems. In this study, we focused on direct measurements of electromagnetic energy transports in the mesoscopic regions and constructed a scanning tunnelling microscope-assisted multi-probe scanning near-field optical microscope spectroscopy system. After producing an emission energy map through a single-probe measurement, two-probe measurement enables us to observe and analyse carrier transport characteristics. It suggests that exciton generation and transport in the mesoscopic region of semiconductors with quantum structure changes, such as the bias of dopant, affect the excited carrier emission recombination process. The measured probability density of the carrier transported with quantum effects can be used for applications in natural intelligence research by combining it with the analysis using tournament structures. Our developed measurement and analysis methods are expected to clarify the details of carrier's behaviour in the mesoscopic region in various materials and lead to applications for novel optoelectronic devices.

Entangled and correlated photon mixed strategy for social decision making.

Collective decision making is important for maximizing total benefits while preserving equality among individuals in the competitive multi-armed bandit (CMAB) problem, wherein multiple players try to gain higher rewards from multiple slot machines. The CMAB problem represents an essential aspect of applications such as resource management in social infrastructure. In a previous study, we theoretically and experimentally demonstrated that entangled photons can physically resolve the difficulty of the CMAB problem. This decision-making strategy completely avoids decision conflicts while ensuring equality. However, decision conflicts can sometimes be beneficial if they yield greater rewards than non-conflicting decisions, indicating that greedy actions may provide positive effects depending on the given environment. In this study, we demonstrate a mixed strategy of entangled- and correlated-photon-based decision-making so that total rewards can be enhanced when compared to the entangled-photon-only decision strategy. We show that an optimal mixture of entangled- and correlated-photon-based strategies exists depending on the dynamics of the reward environment as well as the difficulty of the given problem. This study paves the way for utilizing both quantum and classical aspects of photons in a mixed manner for decision making and provides yet another example of the supremacy of mixed strategies known in game theory, especially in evolutionary game theory.

Entangled N-photon states for fair and optimal social decision making.

Situations involving competition for resources among entities can be modeled by the competitive multi-armed bandit (CMAB) problem, which relates to social issues such as maximizing the total outcome and achieving the fairest resource repartition among individuals. In these respects, the intrinsic randomness and global properties of quantum states provide ideal tools for obtaining optimal solutions to this problem. Based on the previous study of the CMAB problem in the two-arm, two-player case, this paper presents the theoretical principles necessary to find polarization-entangled N-photon states that can optimize the total resource output while ensuring equality among players. These principles were applied to two-, three-, four-, and five-player cases by using numerical simulations to reproduce realistic configurations and find the best strategies to overcome potential misalignment between the polarization measurement systems of the players. Although a general formula for the N-player case is not presented here, general derivation rules and a verification algorithm are proposed. This report demonstrates the potential usability of quantum states in collective decision making with limited, probabilistic resources, which could serve as a first step toward quantum-based resource allocation systems.

Generation of Schubert polynomial series via nanometre-scale photoisomerization in photochromic single crystal and double-probe optical near-field measurements.

Generation of irregular time series based on physical processes is indispensable in computing and artificial intelligence. In this report, we propose and demonstrate the generation of Schubert polynomials, which are the foundation of versatile permutations in mathematics, via optical near-field processes introduced in a photochromic crystal of diarylethene combined with a simple photon detection protocol. Optical near-field excitation on the surface of a photochromic single crystal yields a chain of local photoisomerization, forming a complex pattern on the opposite side of the crystal. The incoming photon travels through the nanostructured photochromic crystal, and the exit position of the photon exhibits a versatile pattern. We emulated trains of photons based on the optical pattern experimentally observed through double-probe optical near-field microscopy, where the detection position was determined based on a simple protocol, leading to Schubert matrices corresponding to Schubert polynomials. The versatility and correlations of the generated Schubert matrices could be reconfigured in either a soft or hard manner by adjusting the photon detection sensitivity. This is the first study of Schubert polynomial generation via physical processes or nanophotonics, paving the way for future nano-scale intelligence devices and systems.

Entangled-photon decision maker.

The competitive multi-armed bandit (CMAB) problem is related to social issues such as maximizing total social benefits while preserving equality among individuals by overcoming conflicts between individual decisions, which could seriously decrease social benefits. The study described herein provides experimental evidence that entangled photons physically resolve the CMAB in the 2-arms 2-players case, maximizing the social rewards while ensuring equality. Moreover, we demonstrated that deception, or outperforming the other player by receiving a greater reward, cannot be accomplished in a polarization-entangled-photon-based system, while deception is achievable in systems based on classical polarization-correlated photons with fixed polarizations. Besides, random polarization-correlated photons have been studied numerically and shown to ensure equality between players and deception prevention as well, although the CMAB maximum performance is reduced as compared with entangled photon experiments. Autonomous alignment schemes for polarization bases were also experimentally demonstrated based only on decision conflict information observed by an individual without communications between players. This study paves a way for collective decision making in uncertain dynamically changing environments based on entangled quantum states, a crucial step toward utilizing quantum systems for intelligent functionalities.

Unique Structural Relaxations and Molecular Conformations of Porphyra-334 at the Excited State.

Quantum chemistry based simulations were used to examine the excited state of porphyra-334, one of the fundamental mycosporine-like amino acids present in a wide variety of aqueous organisms. Our calculations reveal three characteristic aspects of porphyra-334 related to either its ground or excited state. Specifically, (i) the ground state (S0) structure consists of a planar geometry in which three units can be identified, the central cyclohexene ring, the glycine branch, and the threonine branch, reflecting the π conjugation of the system; (ii) the first singlet excited state (S1) shows a large oscillator strength and a typical ππ* excitation character; and (iii) upon relaxation at S1, the originally ground state planar structure undergoes a relaxation to a nonplanar one, S1, especially at the carbon-nitrogen (CN) groups linking the cyclohexene ring to the glycine or threonine arm. The induced nonplanarity can be ascribed to the fact that the carbon atoms of the CN groups prefer an sp3 hybridization in the S1 state. At the singlet state, these processes are unlikely to be trapped by singlet-triplet intersystem crossing especially when these occur in the hydrophilic zwitter-ion forms of porphyra-334. These results provide the missing information for thorough interpretation of the stability of porphyra-334 upon UV irradiation.

Author Correction: Nanometre-scale pattern formation on the surface of a photochromic crystal by optical near-field induced photoisomerization.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Why is the environment important for decision making? Local reservoir model for choice-based learning.

Decision making based on behavioral and neural observations of living systems has been extensively studied in brain science, psychology, neuroeconomics, and other disciplines. Decision-making mechanisms have also been experimentally implemented in physical processes, such as single photons and chaotic lasers. The findings of these experiments suggest that there is a certain common basis in describing decision making, regardless of its physical realizations. In this study, we propose a local reservoir model to account for choice-based learning (CBL). CBL describes decision consistency as a phenomenon where making a certain decision increases the possibility of making that same decision again later. This phenomenon has been intensively investigated in neuroscience, psychology, and other related fields. Our proposed model is inspired by the viewpoint that a decision is affected by its local environment, which is referred to as a local reservoir. If the size of the local reservoir is large enough, consecutive decision making will not be affected by previous decisions, thus showing lower degrees of decision consistency in CBL. In contrast, if the size of the local reservoir decreases, a biased distribution occurs within it, which leads to higher degrees of decision consistency in CBL. In this study, an analytical approach for characterizing local reservoirs is presented, as well as several numerical demonstrations. Furthermore, a physical architecture for CBL based on single photons is discussed, and the effects of local reservoirs are numerically demonstrated. Decision consistency in human decision-making tasks and in recruiting empirical data is evaluated based on the local reservoir. This foundation based on a local reservoir offers further insights into the understanding and design of decision making.

Nanometre-scale pattern formation on the surface of a photochromic crystal by optical near-field induced photoisomerization.

We observed nanometre-scale optical near-field induced photoisomerization on the surface of a photochromic diarylethene crystal via molecular structural changes using an optical near-field assisted atomic force microscope. A nanometre-scale concavity was formed on the sample surface due to locally induced photoisomerization. By using this optical near-field induced local photoisomerization, we succeeded in generating a pattern of alphabet characters on the surface of the diarylethene crystal below the optical wavelength scale. Further, by exploiting the photochromism of the investigated material, erasure of the generated pattern was also confirmed, where the evolution of the pattern during erasure depended on the local spatial characteristics of the crystal. These experimental findings demonstrate the fundamental abilities of photochromic crystals in dynamic memorization in nanometre-scale light-matter interactions.

Scalable photonic reinforcement learning by time-division multiplexing of laser chaos.

Reinforcement learning involves decision-making in dynamic and uncertain environments and constitutes a crucial element of artificial intelligence. In our previous work, we experimentally demonstrated that the ultrafast chaotic oscillatory dynamics of lasers can be used to efficiently solve the two-armed bandit problem, which requires decision-making concerning a class of difficult trade-offs called the exploration-exploitation dilemma. However, only two selections were employed in that research; hence, the scalability of the laser-chaos-based reinforcement learning should be clarified. In this study, we demonstrated a scalable, pipelined principle of resolving the multi-armed bandit problem by introducing time-division multiplexing of chaotically oscillated ultrafast time series. The experimental demonstrations in which bandit problems with up to 64 arms were successfully solved are presented where laser chaos time series significantly outperforms quasiperiodic signals, computer-generated pseudorandom numbers, and coloured noise. Detailed analyses are also provided that include performance comparisons among laser chaos signals generated in different physical conditions, which coincide with the diffusivity inherent in the time series. This study paves the way for ultrafast reinforcement learning by taking advantage of the ultrahigh bandwidths of light wave and practical enabling technologies.

Aphasia Following Left Putaminal Hemorrhage at a Rehabilitation Hospital.

OBJECTIVE: We aimed to clarify the relationship between aphasia and hematoma type/volume in patients with left putaminal hemorrhage admitted to a rehabilitation facility. METHODS: We evaluated the relationship between the presence, type, and severity of aphasia and hematoma type/volume in 92 patients with putaminal hemorrhage aged 29-83 years. Hematoma type and volume were evaluated on the basis of CT images obtained at stroke onset. The Standard Language Test for Aphasia was conducted as part of the initial assessment. RESULTS: Aphasia was observed in 79 of 92 patients. A total of 31 patients had fluent aphasia, while 48 had non-fluent aphasia. Non-fluent aphasia often involved hematoma on the anterior limb of the internal capsule, while fluent aphasia often involved hematoma on the posterior limb of internal capsule. When the hematoma volume exceeded 20 mL, patients experienced difficulty in repeating spoken words. When hematoma volume exceeded 40 mL, non-fluent aphasia was observed in all patients. CONCLUSION: Our findings suggest that hematoma type and volume not only influence the development of aphasia following putaminal hemorrhage but also play a major role in determining the patient's fluency and repetition ability.

Factors necessary for independent walking in patients with thalamic hemorrhage.

BACKGROUND: Thalamic hemorrhages cause motor paralysis, sensory impairment, and cognitive dysfunctions, all of which may significantly affect walking independence. We examined the factors related to independent walking in patients with thalamic hemorrhage who were admitted to a rehabilitation hospital. METHODS: We evaluated 128 patients with thalamic hemorrhage (75 men and 53 women; age range, 40-93 years) who were admitted to our rehabilitation hospital. The mean duration from symptom onset to rehabilitation hospital admission was 27.2 ± 10.3 days, and the mean rehabilitation hospital stay was 71.0 ± 31.4 days. Patients' neurological and cognitive functions were examined with the National Institutes of Health Stroke Scale (NIHSS) and Mini-Mental State Examination (MMSE), respectively. The relationship between patients' scores on these scales and their walking ability at discharge from the rehabilitation hospital was analyzed. Additionally, a decision-tree analysis was used to create a model for predicting independent walking upon referral to the rehabilitation hospital. RESULTS: Among the patients, 65 could walk independently and 63 could not. The two patient groups were significantly different in terms of age, duration from symptom onset to rehabilitation hospital admission, hematoma type, hematoma volume, neurological symptoms, and cognitive function. The decision-tree analysis revealed that the patient's age, NIHSS score, MMSE score, hematoma volume, and presence of ventricular bleeding were factors that could predict independent walking. CONCLUSIONS: In patients with thalamic hemorrhage, the neurological symptoms, cognitive function, and neuroimaging factors at onset are useful for predicting independent walking.

How seaweeds release the excess energy from sunlight to surrounding sea water.

We report an atomistic insight into the mechanism regulating the energy released by a porphyra-334 molecule, the ubiquitous photosensitive component of marine algae, in a liquid water environment upon an electron excitation. To quantify this rapidly occurring process, we resort to the Fourier analysis of the mass-weighted auto-correlation function, providing evidence for a remarkable dynamic change in the number of hydrogen bonds among water molecules and between the porphyra-334 and its surrounding hydrating water. Hydrogen bonds between the porphyra-334 and close by water molecules can act directly and rather easily to promote an efficient transfer of the excess kinetic energies of the porphyra-334 to the surrounding solvating water molecules via an activation of the collective modes identified as hydrogen-bond stretching modes in liquid water which eventually results in a disruption of the hydrogen bond network. Since porphyra-334 is present in seaweeds, aquatic cyanobacteria (blue-green algae) and red algae, our findings allow addressing the question how algae in oceans or lakes, upon sunlight absorption, can release large amounts of energy into surrounding water without destabilizing neither their own nor the H2O molecular structure.

Random walk with chaotically driven bias.

We investigate two types of random walks with a fluctuating probability (bias) in which the random walker jumps to the right. One is a 'time-quenched framework' using bias time series such as periodic, quasi-periodic, and chaotic time series (chaotically driven bias). The other is a 'time-annealed framework' using the fluctuating bias generated by a stochastic process, which is not quenched in time. We show that the diffusive properties in the time-quenched framework can be characterised by the ensemble average of the time-averaged variance (ETVAR), whereas the ensemble average of the time-averaged mean square displacement (ETMSD) fails to capture the diffusion, even when the total bias is zero. We demonstrate that the ETVAR increases linearly with time, and the diffusion coefficient can be estimated by the time average of the local diffusion coefficient. In the time-annealed framework, we analytically and numerically show normal diffusion and superdiffusion, similar to the Lévy walk. Our findings will lead to new developments in information and communication technologies, such as efficient energy transfer for information propagation and quick solution searching.

Single-photon decision maker.

Decision making is critical in our daily lives and for society in general and is finding evermore practical applications in information and communication technologies. Herein, we demonstrate experimentally that single photons can be used to make decisions in uncertain, dynamically changing environments. Using a nitrogen-vacancy in a nanodiamond as a single-photon source, we demonstrate the decision-making capability by solving the multi-armed bandit problem. This capability is directly and immediately associated with single-photon detection in the proposed architecture, leading to adequate and adaptive autonomous decision making. This study makes it possible to create systems that benefit from the quantum nature of light to perform practical and vital intelligent functions.

Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer.

By using nanoscale energy-transfer dynamics and density matrix formalism, we demonstrate theoretically and numerically that chaotic oscillation and random-number generation occur in a nanoscale system. The physical system consists of a pair of quantum dots (QDs), with one QD smaller than the other, between which energy transfers via optical near-field interactions. When the system is pumped by continuous-wave radiation and incorporates a timing delay between two energy transfers within the system, it emits optical pulses. We refer to such QD pairs as nano-optical pulsers (NOPs). Irradiating an NOP with external periodic optical pulses causes the oscillating frequency of the NOP to synchronize with the external stimulus. We find that chaotic oscillation occurs in the NOP population when they are connected by an external time delay. Moreover, by evaluating the time-domain signals by statistical-test suites, we confirm that the signals are sufficiently random to qualify the system as a random-number generator (RNG). This study reveals that even relatively simple nanodevices that interact locally with each other through optical energy transfer at scales far below the wavelength of irradiating light can exhibit complex oscillatory dynamics. These findings are significant for applications such as ultrasmall RNGs.

Optical near-field-mediated polarization asymmetry induced by two-layer nanostructures.

We demonstrate that a two-layer shape-engineered nanostructure exhibits asymmetric polarization conversion efficiency thanks to near-field interactions. We present a rigorous theoretical foundation based on an angular-spectrum representation of optical near-fields that takes account of the geometrical features of the proposed device architecture and gives results that agree well with electromagnetic numerical simulations. The principle used here exploits the unique intrinsic optical near-field processes associated with nanostructured matter, while eliminating the need for conventional scanning optical fiber probing tips, paving the way to novel nanophotonic devices and systems.

Amoeba-inspired nanoarchitectonic computing: solving intractable computational problems using nanoscale photoexcitation transfer dynamics.

Biologically inspired computing devices and architectures are expected to overcome the limitations of conventional technologies in terms of solving computationally demanding problems, adapting to complex environments, reducing energy consumption, and so on. We previously demonstrated that a primitive single-celled amoeba (a plasmodial slime mold), which exhibits complex spatiotemporal oscillatory dynamics and sophisticated computing capabilities, can be used to search for a solution to a very hard combinatorial optimization problem. We successfully extracted the essential spatiotemporal dynamics by which the amoeba solves the problem. This amoeba-inspired computing paradigm can be implemented by various physical systems that exhibit suitable spatiotemporal dynamics resembling the amoeba's problem-solving process. In this Article, we demonstrate that photoexcitation transfer phenomena in certain quantum nanostructures mediated by optical near-field interactions generate the amoebalike spatiotemporal dynamics and can be used to solve the satisfiability problem (SAT), which is the problem of judging whether a given logical proposition (a Boolean formula) is self-consistent. SAT is related to diverse application problems in artificial intelligence, information security, and bioinformatics and is a crucially important nondeterministic polynomial time (NP)-complete problem, which is believed to become intractable for conventional digital computers when the problem size increases. We show that our amoeba-inspired computing paradigm dramatically outperforms a conventional stochastic search method. These results indicate the potential for developing highly versatile nanoarchitectonic computers that realize powerful solution searching with low energy consumption.