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Article
Open AccessHistory-dependent nano-photoisomerization by optical near-field in photochromic single crystals
The history dependence of physical systems is promising for solving complex problems. To exploit spontaneous nanometre-scale optical memory for computation, the history dependence must be elucidated. Here, we ...
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Article
Open AccessConflict-free joint decision by lag and zero-lag synchronization in laser network
With the end of Moore’s Law and the increasing demand for computing, photonic accelerators are garnering considerable attention. This is due to the physical characteristics of light, such as high bandwidth and...
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Article
Open AccessSingle-shot blind deconvolution in coherent diffraction imaging with coded aperture
We present a method for single-shot blind deconvolution in coherent diffraction imaging. Coherent diffraction imaging is a technique for non-interferometric quantitative phase imaging without reference light. ...
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Article
Open AccessAsymmetric quantum decision-making
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. Quantu...
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Article
Coherent diffraction imaging through shift-invariant scattering
In this paper, we present a method for single-shot phase imaging with a wide field of view based on coherent diffraction imaging. Coherent diffraction imaging can be implemented by compact optical hardware wit...
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Article
Open AccessOrder 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 process...
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Article
Open AccessDecision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers
Decision making using photonic technologies has been intensively researched for solving the multi-armed bandit problem, which is fundamental to reinforcement learning. However, these technologies are yet to be...
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Article
Open AccessConflict-free collective stochastic decision making by orbital angular momentum of photons through quantum interference
In recent cross-disciplinary studies involving both optics and computing, single-photon-based decision-making has been demonstrated by utilizing the wave-particle duality of light to solve multi-armed bandit p...
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Article
Open AccessEntangled 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 high...
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Article
Open AccessArm order recognition in multi-armed bandit problem with laser chaos time series
By exploiting ultrafast and irregular time series generated by lasers with delayed feedback, we have previously demonstrated a scalable algorithm to solve multi-armed bandit (MAB) problems utilizing the time-d...
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Article
Open AccessEntangled 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 achiev...
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Article
Open AccessAdaptive model selection in photonic reservoir computing by reinforcement learning
Photonic reservoir computing is an emergent technology toward beyond-Neumann computing. Although photonic reservoir computing provides superior performance in environments whose characteristics are coincident ...
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Article
Open AccessGeneration 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, whi...
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Article
Open AccessDynamic channel selection in wireless communications via a multi-armed bandit algorithm using laser chaos time series
Dynamic channel selection is among the most important wireless communication elements in dynamically changing electromagnetic environments wherein, a user can experience improved communication quality by choos...
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Article
Open AccessGenerative adversarial network based on chaotic time series
Generative adversarial networks (GANs) are becoming increasingly important in the artificial construction of natural images and related functionalities, wherein two types of networks called generators and disc...
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Article
Open AccessEntangled-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 dec...
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Article
Open AccessOn-chip photonic decision maker using spontaneous mode switching in a ring laser
Efficient and accurate decision making is gaining increased importance with the rapid expansion of information communication technologies including artificial intelligence. Here, we propose and experimentally ...
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Article
Open AccessAuthor 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.
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Article
Open AccessNanometre-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 forc...
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Article
Open AccessScalable 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...
