Search

Integrated photonic quantum information processing (QIP) has advanced rapidly due to progress in various nanophotonic platforms. Single photon detectors have been the subject of intense study due to their ubiquity in QIP systems, yet many state-of-the art detectors operate at cryogenic temperatures under vacuum and suffer from long dead times. We propose and demonstrate a single photon detection scheme based on optical parametric amplification in nanophotonic lithium niobate (LN) combined with a classical photodetector. We use quantum detector tomography and experimentally demonstrate an efficiency of 26.5% with a 2.2% dark count rate. We show that by improving the nonlinearity-to-loss ratio in nanophotonics and using homodyne detection on a squeezed pump, the detector can achieve 69% efficiency with 0.9% dark count rate. The detector operates at room temperature, has no intrinsic dead time, and is readily integrated in LN nanophotonics, in which many other components of photonic QIP are available. Our results represent a step towards all-optical ultrafast photon detection for scalable nanophotonic QIP., Comment: 15 pages, 7 figures

This paper studies an asset pricing model in a partially observable market with a large number of heterogeneous agents using the mean field game theory. In this model, we assume that investors can only observe stock prices and must infer the risk premium from these observations when determining trading strategies. We characterize the equilibrium risk premium in such a market through a solution to the mean field backward stochastic differential equation (BSDE). Specifically, the solution to the mean field BSDE can be expressed semi-analytically by employing an exponential quadratic Gaussian framework. We then construct the risk premium process, which cannot be observed directly by investors, endogenously using the Kalman-Bucy filtering theory. In addition, we include a simple numerical simulation to visualize the dynamics of our market model., Comment: 22 pages, 5 figures

In e-commerce platforms, coupons play a crucial role in boosting transactions. In the customer-to-customer (C2C) marketplace, ensuring the satisfaction of both buyers and sellers is essential. While buyer-focused marketing strategies often receive more attention, addressing the needs of sellers is equally important. Additionally, the existing strategies tend to optimize each promotion independently, resulting in a lack of continuity between promotions and unnecessary costs in the pursuit of short-term impact within each promotion period. We introduce a Dynamic Sequential Coupon Allocation Framework (DSCAF) to optimize item coupon allocation strategies across a series of promotions. DSCAF provides sequential recommendations for coupon configurations and timing to target items. In cases where initial suggestions do not lead to sales, it dynamically adjusts the strategy and offers subsequent solutions. It integrates two predictors for estimating the sale propensity in the current and subsequent rounds of coupon allocation, and a decision-making process to determine the coupon allocation solution. It runs iteratively until the item is sold. The goal of the framework is to maximize Return on Investment (ROI) while ensuring lift Sell-through Rate (STR) remains above a specified threshold. DSCAF aims to optimize sequential coupon efficiency with a long-term perspective rather than solely focusing on the lift achieved in each individual promotion. It has been applied for item coupon allocation in Mercari.

In a two-sided marketplace, network effects are crucial for competitiveness, and platforms need to retain users through advanced customer relationship management as much as possible. Maintaining numerous providers' stable and active presence on the platform is highly important to enhance the marketplace's scale and diversity. The strongest motivation for providers to continue using the platform is to realize actual profits through sales. Then, we propose a personalized promotion to increase the number of successful providers with sales experiences on the platform. The main contributions of our research are twofold. First, we introduce a new perspective in provider management with the distribution of successful sales experiences. Second, we propose a personalized promotion optimization method to maximize the number of providers' sales experiences. By utilizing this approach, we ensure equal opportunities for providers to experience sales without being monopolized by a few providers. Through experiments using actual data on coupon distribution, we confirm that our method enables the implementation of coupon allocation strategies that significantly increase the total number of providers having sales experiences., Comment: 8 pages, 10 figures, KDD 2024 Workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth

This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and strong Japanese LLMs, and as of this writing, more than 1,500 participants from academia and industry are working together for this purpose. This paper presents the background of the establishment of LLM-jp, summaries of its activities, and technical reports on the LLMs developed by LLM-jp. For the latest activities, visit https://llm-jp.nii.ac.jp/en/.

This paper presents an asset pricing model in an incomplete market involving a large number of heterogeneous agents based on the mean field game theory. In the model, we incorporate habit formation in consumption preferences, which has been widely used to explain various phenomena in financial economics. In order to characterize the market-clearing equilibrium, we derive a quadratic-growth mean field backward stochastic differential equation (BSDE) and study its well-posedness and asymptotic behavior in the large population limit. Additionally, we introduce an exponential quadratic Gaussian reformulation of the asset pricing model, in which the solution is obtained in a semi-analytic form., Comment: Forthcoming in Asia-Pacific Financial Markets. 34 pages

Arrays of nonlinear resonators offer a fertile ground for a wide range of complex phenomena and opportunities for advanced photonic sensing and computing. Recently, significant attention has focused on studying coupled resonators in special-purpose configurations either on chips or in table-top experiments. However, a path to realizing a large-scale programmable network of nonlinear photonic resonators remains elusive because of the challenges associated with simultaneously achieving strong nonlinearity, independent operation of the resonators, and programmability of the couplings. In this work, we break these barriers by realizing large-scale, time-multiplexed optical parametric oscillators (OPOs) on a single lithium niobate nanophotonic chip. We show independent operation of 70 identical OPOs in an ultrafast nanophotonic circuit. The OPOs exhibit an ultra-low threshold of a few picojoules, substantially surpassing the strength of nonlinearity of other platforms. Using our ultrafast nanophotonic circuit, a network of N OPOs with programmable all-to-all couplings requires only a few additional components. The time-multiplexed nanophotonic OPOs can enable myriad applications, including ultrafast classical and quantum information processing., Comment: 19 pages, 5 figures

We investigate the impact of politeness levels in prompts on the performance of large language models (LLMs). Polite language in human communications often garners more compliance and effectiveness, while rudeness can cause aversion, impacting response quality. We consider that LLMs mirror human communication traits, suggesting they align with human cultural norms. We assess the impact of politeness in prompts on LLMs across English, Chinese, and Japanese tasks. We observed that impolite prompts often result in poor performance, but overly polite language does not guarantee better outcomes. The best politeness level is different according to the language. This phenomenon suggests that LLMs not only reflect human behavior but are also influenced by language, particularly in different cultural contexts. Our findings highlight the need to factor in politeness for cross-cultural natural language processing and LLM usage., Comment: SICon 2024

Hemodynamic parameters are often estimated assuming a constant Newtonian viscosity, even though blood exhibits shear-thinning behavior. This article investigates the influence of blood rheology and hematocrit (Hct) percentage on the estimation of Wall Shear Stress (WSS), rate of viscous Energy Loss ($\dot{E}_L$) at different points in the cardiac cycle, and the Oscillatory Shear Index (OSI). We focus on a hematocrit-dependent power-law non-Newtonian model, considering a wide range of Hct values at physiological temperature, with rheological parameters obtained from previously reported experimental data. In all cases, we systematically compared WSS, $\dot{E}_L$, and OSI using both Newtonian and power-law models, underscoring the crucial role of blood rheology in accurately assessing cardiovascular diseases. Our results show that, in in-silico experiments, differences in WSS and $\dot{E}_L$ across a wide range of Hct values can reach as high as 190\% and 113\% at systole, and as low as -72\% and -74\% at diastole, respectively. In in-vivo data, differences in WSS and $\dot{E}_L$ can reach up to -45\% and -60\% at systole, and range from -69\% to 73\% at diastole. This study enhances our understanding of the impact of blood rheology on hemodynamic parameter estimations using both in-silico and in-vivo aortic 4D Flow MRI data.

Photonics offers unique capabilities for quantum information processing (QIP) such as room-temperature operation, the scalability of nanophotonics, and access to ultrabroad bandwidths and consequently ultrafast operation. Ultrashort-pulse sources of quantum states in nanophotonics are an important building block for achieving scalable ultrafast QIP, however, their demonstrations so far have been sparse. Here, we demonstrate a femtosecond biphoton source in dispersion-engineered periodically poled lithium niobate nanophotonics. We measure 17 THz of bandwidth for the source centered at 2.09 \textmu m, corresponding to a few optical cycles, with a brightness of 8.8 GHz/mW. Our results open new paths towards realization of ultrafast nanophotonic QIP.

We study backward stochastic difference equations (BS{\Delta}E) driven by a d-dimensional stochastic process on a lattice whose increments have only d + 1 possible values that generates the lattice. Regarding the driving process as a d dimensional asset price process, we give applications to an optimal investment problem and a market equilibrium analysis, where utility functionals are defined through BS{\Delta}E.

The quantum transduction between microwave and optical photons is essential for realizing scalable quantum computers with superconducting qubits. Due to the large frequency difference between microwave and optical ranges, the transduction needs to be done via intermediate bosonic modes or nonlinear processes. So far, the transduction efficiency $\eta$ via the magneto-optic Faraday effect (i.e., the light-magnon interaction) in the ferromagnet YIG has been demonstrated to be small as $\eta\sim 10^{-8} \mathrm{-} 10^{-15}$ due to the weak magneto-optic coupling. Here, we take advantage of the fact that three-dimensional topological insulator thin films exhibit a topological Faraday effect that is independent of the sample thickness in the terahertz regime. This leads to a large Faraday rotation angle and therefore enhanced light-magnon interaction in the thin film limit. We show theoretically that the transduction efficiency between microwave and terahertz photons can be greatly improved to $\eta\sim10^{-4}$ by utilizing the heterostructures consisting of topological insulator thin films such as Bi$_2$Se$_3$ and ferromagnetic insulator thin films such as YIG., Comment: 11 pages, 7 figures. To appear in Phys. Rev. Applied

To reduce the typical time-consuming routines of plant modeling for model-based controller designs, the fictitious reference iterative tuning (FRIT) has been proposed and has proven to be effective in many applications. However, it is generally difficult to select a reference model properly without information on the plant, which significantly affects the control performance and sometimes leads to considerable performance degradation. To address this problem, we propose a pseudo-linearization (PL) method using FRIT and design a new controller for nonlinear systems that combines data-driven and model-based control. This design considers the input constraints using model predictive control. The effectiveness of the proposed method was evaluated according to several practical references using numerical simulations for nonlinear classes and experiments involving artificial muscles with hysteresis characteristics., Comment: 11 pages, 16 figures, 4 tables, To be submitted to IET Control Theory & Applications

Lithium niobate (LiNbO$_3$, LN) is a ferroelectric crystal of interest for integrated photonics owing to its large second-order optical nonlinearity and the ability to impart periodic poling via an external electric field. However, on-chip device performance based on thin-film lithium niobate (TFLN) is presently limited by propagation losses arising from surface roughness and corrugations. Atomic layer etching (ALE) could potentially smooth these features and thereby increase photonic performance, but no ALE process has been reported for LN. Here, we report an isotropic ALE process for $x$-cut MgO-doped LN using sequential exposures of H$_2$ and SF$_6$/Ar plasmas. We observe an etch rate of $1.59 \pm 0.02$ nm/cycle with a synergy of $96.9$%. We also demonstrate ALE can be achieved with SF$_6$/O$_2$ or Cl$_2$/BCl$_3$ plasma exposures in place of the SF$_6$/Ar plasma step with synergies of $99.5$% and $91.5$% respectively. The process is found to decrease the sidewall surface roughness of TFLN waveguides etched by physical Ar$^+$ milling by 30% without additional wet processing. Our ALE process could be used to smooth sidewall surfaces of TFLN waveguides as a post-processing treatment, thereby increasing the performance of TFLN nanophotonic devices and enabling new integrated photonic device capabilities.

Efficient on-chip entangled photon pair generation at telecom wavelengths is an integral aspect of emerging quantum optical technologies, particularly for quantum communication and computing. However, moving to shorter wavelengths enables the use of more accessible silicon detector technology and opens up applications in imaging and spectroscopy. Here, we present high brightness ($(1.6 \pm 0.3) \times 10^{9}$ pairs/mW/nm) visible-near-IR photon pair generation in a periodically poled lithium niobate nanophotonic waveguide. The degenerate spectrum of the photon pairs is centered at 811 nm with a bandwidth of 117 nm. The measured on-chip source efficiency of $(2.3\pm 0.5) \times 10^{11}$ pairs/mW is on par with source efficiencies at telecom wavelengths and is also orders of magnitude higher than the efficiencies of other visible sources implemented in bulk crystal or diffused waveguide-based technologies. These results represent the shortest wavelength of photon pairs generated in a nanophotonic waveguide reported to date by nearly an octave., Comment: Main text: 10 pages, 6 figures; Supplementary material: 5 pages, 3 figures. Author initials updated