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We study the effect of acceleration and deceleration on the stability of channel flows. To do so, we derive an exact solution for laminar profiles of channel flows with arbitrary, time-varying wall motion and pressure gradient. This solution then allows us to investigate the stability of any unsteady channel flow. In particular, we restrict our investigation to the nonnormal growth of perturbations about time-varying base flows with exponentially decaying acceleration and deceleration, with comparisons to growth about a constant base flow (i.e., the time-invariant simple shear or parabolic profile). We apply this acceleration and deceleration through the velocity of the walls and through the flow rate. For accelerating base flows, perturbations never grow larger than perturbations about a constant base flow, while decelerating flows show massive amplification of perturbations - at a Reynolds number of 500, properly timed perturbations about the decelerating base flow grow $\mathscr{O}(10^5)$ times larger than perturbations grow about a constant base flow. This amplification increases as we raise the rate of deceleration and the Reynolds number. We find that this amplification arises due to a transition from spanwise perturbations leading to the largest amplification, to streamwise perturbations leading to the largest amplification that only occurs in the decelerating base flow. By evolving the optimal perturbations through the linearized equations of motion, we reveal that the decelerating base flow achieves this massive amplification through the Orr mechanism, or the down-gradient Reynolds stress mechanism, which accelerating and constant base flows cannot maintain.

We investigate the black hole mass function (BHMF) and Eddington ratio distribution function (ERDF) of broad-line AGNs at z=4, based on a sample of 52 quasars with i<23.2 at 3.50 < z < 4.25 from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) S16A-Wide2 dataset, and 1,462 quasars with i<20.2 in the same redshift range from the Sloan Digital Sky Survey (SDSS) DR7 quasar catalog. Virial BH masses of quasars are estimated using the width of the CIV 1549{\AA} line and the continuum luminosity at 1350{\AA}. To obtain the intrinsic broad-line AGN BHMF and ERDF, we correct for the incompleteness in the low-mass and/or low-Eddington-ratio ranges caused by the flux-limited selection. The resulting BHMF is constrained down to $\log M_{\rm BH}/M_{\odot}\sim7.5$. In comparison with broad-line AGN BHMFs at z=2 in the literature, we find that the number density of massive SMBHs peaks at higher redshifts, consistent with the "down-sizing" evolutionary scenario. Additionally, the resulting ERDF shows a negative dependence on BH mass, suggesting more massive SMBHs tend to accrete at lower Eddington ratios at z=4. With the derived intrinsic broad-line AGN BHMF, we also evaluate the active fraction of broad-line AGNs among the entire SMBH population at z=4. The resulting active fraction may suggest a positive dependence on BH mass. Finally, we examine the time evolution of broad-line AGN BHMF between z=4 and 6 through solving the continuity equation. The results suggest that the broad-line AGN BHMFs at z=4-6 only show evolution in their normalization, but with no significant changes in their shape., Comment: 38 pages, 26 figures. Submitted to ApJ. Data is available in https://github.com/wanqqq31/BHMF_hsc_z4

Quantum superposition of high-dimensional states enables both computational speed-up and security in cryptographic protocols. However, the exponential complexity of tomographic processes makes certification of these properties a challenging task. In this work, we experimentally certify coherence witnesses tailored for quantum systems of increasing dimension, using pairwise overlap measurements enabled by a six-mode universal photonic processor fabricated with a femtosecond laser writing technology. In particular, we show the effectiveness of the proposed coherence and dimension witnesses for qudits of dimensions up to 5. We also demonstrate advantage in a quantum interrogation task, and show it is fueled by quantum contextuality. Our experimental results testify to the efficiency of this novel approach for the certification of quantum properties in programmable integrated photonic platforms, Comment: 9 pages, 5 figures + Supplementary Information

Quantum state teleportation represents a pillar of quantum information and a milestone on the roadmap towards quantum networks with a large number of nodes. Successful photonic demonstrations of this protocol have been carried out employing different qubit encodings. However, demonstrations in the Fock basis encoding are challenging, due to the impossibility of creating a coherent superposition of vacuum-one photon states on a single mode with linear optics. Previous realizations using such an encoding strongly relied on ancillary modes of the electromagnetic field, which only allowed the teleportation of subsystems of entangled states. Here, we enable quantum teleportation of genuine vacuum-one photon states avoiding ancillary modes, by exploiting coherent control of a resonantly excited semiconductor quantum dot in a micro-cavity. Within our setup, we can teleport vacuum-one-photon qubits and perform entanglement swapping in such an encoding. Our results may disclose new potentialities of quantum dot single-photon sources for quantum information applications., Comment: 10 pages, 4 figures + Supplementary Information

One of the key questions on active galactic nuclei (AGN) in galaxy clusters is how AGN could affect the formation and evolution of member galaxies and galaxy clusters in the history of the Universe. To address this issue, we investigate the dependence of AGN number fraction ($f_{\rm AGN}$) on cluster redshift ($z_{\rm cl}$) and distance from the cluster center ($R/R_{\rm 200}$). We focus on more than 27,000 galaxy groups and clusters at $0.1 < z_{\rm cl} < 1.4$ with more than 1 million member galaxies selected from the Subaru Hyper Suprime-Cam. By combining various AGN selection methods based on infrared (IR), radio, and X-ray data, we identify 2,688 AGN. We find that (i) $f_{\rm AGN}$ increases with $z_{\rm cl}$ and (ii) $f_{\rm AGN}$ decreases with $R/R_{\rm 200}$. The main contributors to the rapid increase of $f_{\rm AGN}$ towards high-$z$ and cluster center are IR- and radio-selected AGN, respectively. Those results indicate that the emergence of the AGN population depends on the environment and redshift, and galaxy groups and clusters at high-$z$ play an important role in AGN evolution. We also find that cluster-cluster mergers may not drive AGN activity in at least the cluster center, while we have tentative evidence that cluster-cluster mergers would enhance AGN activity in the outskirts of (particularly massive) galaxy clusters., Comment: 16 pages, 21 figures, and 2 tables, accepted for publication in PASJ

The JSNS$^{2}$ (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment designed for the search for sterile neutrinos. The experiment is currently at the stage of the second phase named JSNS$^{2}$-II with two detectors at near and far locations from the neutrino source. One of the key components of the experiment is an acrylic vessel, that is used for the target volume for the detection of the anti-neutrinos. The specifications, design, and measured properties of the acrylic vessel are described.

In this paper, we prove Strichartz estimates for the $(k,a)$-generalized Laguerre operators $a^{-1}(-|x|^{2-a}\Delta_k+|x|^a)$ which were introduced by Ben Sa\"{\i}d-Kobayashi-{\0}rsted, and for the operators $|x|^{2-a}\Delta_k$. Here $k$ denotes a non-negative multiplicity function for the Dunkl Laplacian $\Delta_k$ and $a$ denotes a positive real number satisfying certain conditions. The cases $a=1,2$ were studied previously. We consider more general cases here. The proof depends on symbol-type estimates of special functions and a discrete analog of the stationary phase theorem inspired by the work of Ionescu-Jerison., Comment: 35 pages

Experimental investigations were performed to elucidate the features of flow fields occurring over cantilevered finite-aspect ratio NACA 0015 wings at high angles of attack with various sweep angles and taper ratios. Volumetric Stereoscopic Particle Image Velocimetry experiments were performed at mean chord based Reynolds number of 247,500 in a wind tunnel and 600 in a water tunnel. Direct Numerical Simulations (DNS) of the water tunnel test section, including the cantilevered model, were also performed at the lower Reynolds number. The low Reynolds number experiments, low Reynolds number simulations, and high Reynolds number experiments all showed that sweeping the leading edge back shifted the largest portion of the reversed flow towards the wingtip while sweeping the trailing edge forward shifted the reversed flow towards the wing root. A detailed parametric sweep of planform geometry systematically varied the leading and trailing edge sweep angles and taper ratios of the finite wings. It was found that the large scale vortical structures resulting from varying these parameters at the two Reynolds numbers share surprisingly many three-dimensional topological features, despite the orders of magnitude different Reynolds numbers.

Recent developments have led to the possibility of embedding machine learning tools into experimental platforms to address key problems, including the characterization of the properties of quantum states. Leveraging on this, we implement a quantum extreme learning machine in a photonic platform to achieve resource-efficient and accurate characterization of the polarization state of a photon. The underlying reservoir dynamics through which such input state evolves is implemented using the coined quantum walk of high-dimensional photonic orbital angular momentum, and performing projective measurements over a fixed basis. We demonstrate how the reconstruction of an unknown polarization state does not need a careful characterization of the measurement apparatus and is robust to experimental imperfections, thus representing a promising route for resource-economic state characterisation.

JSNS$^2$ (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment which searches for sterile neutrinos via the observation of $\bar{\nu}_{\mu} \to \bar{\nu}_{e}$ appearance oscillations using muon decay-at-rest neutrinos. The data taking of JSNS$^2$ have been performed from 2021. In this manuscript, a study of the accidental background is presented. The rate of the accidental background is (9.29$\pm 0.39) \times 10^{-8}$ / spill with 0.75 MW beam power and comparable to the number of searching signals., Comment: arXiv admin note: substantial text overlap with arXiv:2111.07482

Single-photon sources based on semiconductor quantum dots find several applications in quantum information processing due to their high single-photon indistinguishability, on-demand generation, and low multiphoton emission. In this context, the generation of entangled photons represents a challenging task with a possible solution relying on the interference in probabilistic gates of identical photons emitted at different pulses from the same source. In this work, we implement this approach via a simple and compact design that generates entangled photon pairs in the polarization degree of freedom. We operate the proposed platform with single photons produced through two different pumping schemes, the resonant excited one and the longitudinal-acoustic phonon-assisted configuration. We then characterize the produced entangled two-photon states by developing a complete model taking into account relevant experimental parameters, such as the second-order correlation function and the Hong-Ou-Mandel visibility. Our source shows long-term stability and high quality of the generated entangled states, thus constituting a reliable building block for optical quantum technologies.

Large amplitude gust encounters exhibit a range of separated flow phenomena, making them difficult to characterize using the traditional tools of aerodynamics. In this work, we propose a dynamical systems approach to gust encounters, viewing the flow as a cycle (or a closed trajectory) in state space. We posit that the topology of this cycle, or its shape and structure, provides a compact description of the flow, and can be used to identify coordinates in which the dynamics evolve in a simple, intuitive way. To demonstrate this idea, we consider flowfield measurements of a transverse gust encounter. For each case in the dataset, we characterize the full-state dynamics of the flow using persistent homology, a tool that identifies holes in point cloud data, and transform the dynamics to a reduced-order space using a nonlinear autoencoder. Critically, we constrain the autoencoder such that it preserves topologically relevant features of the original dynamics, or those features identified by persistent homology. Using this approach, we are able to transform six separate gust encounters to a three-dimensional latent space, in which each gust encounter reduces to a simple circle, and from which the original flow can be reconstructed. This result shows that topology can guide the creation of low-dimensional state representations for strong transverse gust encounters, a crucial step toward the modeling and control of airfoil-gust interactions.

Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage towards the realization of universal quantum computers. In the context of non-universal noisy intermediate quantum devices, photonic-based sampling machines solving the Gaussian Boson Sampling problem currently play a central role in the experimental demonstration of a quantum computational advantage. In particular, the recently developed photonic machine Borealis, a large-scale instance of a programmable Gaussian Boson Sampling device encoded in the temporal modes of single photons, is available online for external users. In this work, we test the performances of Borealis as a sampling machine and its possible use cases in graph theory. We focused on the validation problem of the sampling process in the presence of experimental noise, such as photon losses, that could undermine the hardness of simulating the experiment. To this end, we used a recent protocol that exploits the connection between Guassian Boson Sampling and graphs perfect match counting. Such an approach to validation also provides connections with the open question on the effective advantage in using noisy Gaussian Boson Sampling devices for graphs similarity and isomorphism problems., Comment: 12 pages, 6 figures

We obtain an optimal actuation waveform for fast synchronization of periodic airfoil wakes through the phase reduction approach. Using the phase reduction approach for periodic wake flows, the spatial sensitivity fields with respect to the phase of the vortex shedding are obtained. The phase sensitivity fields can uncover the synchronization properties in the presence of periodic actuation. This study seeks a periodic actuation waveform using phase-based analysis to minimize the time for synchronization to modify the wake-shedding frequency of NACA0012 airfoil wakes. This fast synchronization waveform is obtained theoretically from the phase sensitivity function by casting an optimization problem. The obtained optimal actuation waveform becomes increasingly non-sinusoidal for higher angles of attack. Actuation based on the obtained waveform achieves rapid synchronization within as low as two vortex shedding cycles irrespective of the forcing frequency whereas traditional sinusoidal actuation requires O(10) shedding cycles. Further, we analyze the influence of actuation frequency on the vortex shedding and the aerodynamic coefficients using force-element analysis. The present analysis provides an efficient way to modify the vortex lock-on properties in a transient manner with applications to fluid-structure interactions and unsteady flow control., Comment: 10 pages, 5 figures

Adaptivity to the difficulties of a problem is a key property in sequential decision-making problems to broaden the applicability of algorithms. Follow-the-regularized-leader (FTRL) has recently emerged as one of the most promising approaches for obtaining various types of adaptivity in bandit problems. Aiming to further generalize this adaptivity, we develop a generic adaptive learning rate, called stability-penalty-adaptive (SPA) learning rate for FTRL. This learning rate yields a regret bound jointly depending on stability and penalty of the algorithm, into which the regret of FTRL is typically decomposed. With this result, we establish several algorithms with three types of adaptivity: sparsity, game-dependency, and best-of-both-worlds (BOBW). Despite the fact that sparsity appears frequently in real problems, existing sparse multi-armed bandit algorithms with $k$-arms assume that the sparsity level $s \leq k$ is known in advance, which is often not the case in real-world scenarios. To address this issue, we first establish $s$-agnostic algorithms with regret bounds of $\tilde{O}(\sqrt{sT})$ in the adversarial regime for $T$ rounds, which matches the existing lower bound up to a logarithmic factor. Meanwhile, BOBW algorithms aim to achieve a near-optimal regret in both the stochastic and adversarial regimes. Leveraging the SPA learning rate and the technique for $s$-agnostic algorithms combined with a new analysis to bound the variation in FTRL output in response to changes in a regularizer, we establish the first BOBW algorithm with a sparsity-dependent bound. Additionally, we explore partial monitoring and demonstrate that the proposed SPA learning rate framework allows us to achieve a game-dependent bound and the BOBW simultaneously., Comment: Published version in Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 32 pages

We present the quasar luminosity function (LF) at $z = 7$, measured with 35 spectroscopically confirmed quasars at $6.55 < z < 7.15$. The sample of 22 quasars from the Subaru High-$z$ Exploration of Low-Luminosity Quasars (SHELLQs) project, combined with 13 brighter quasars in the literature, covers an unprecedentedly wide range of rest-frame ultraviolet magnitudes over $-28 < M_{1450} < -23$. We found that the binned LF flattens significantly toward the faint end populated by the SHELLQs quasars. A maximum likelihood fit to a double power-law model has a break magnitude $M^*_{1450} = -25.60^{+0.40}_{-0.30}$, a characteristic density $\Phi^* = 1.35^{+0.47}_{-0.30}$ Gpc$^{-3}$ mag$^{-1}$, and a bright-end slope $\beta = -3.34^{+0.49}_{-0.57}$, when the faint-end slope is fixed to $\alpha = -1.2$ as observed at $z \le 6$. The overall LF shape remains remarkably similar from $z = 4$ to $7$, while the amplitude decreases substantially toward higher redshifts, with a clear indication of an accelerating decline at $z \ge 6$. The estimated ionizing photon density, $10^{48.2 \pm 0.1}$ s$^{-1}$ Mpc$^{-3}$, is less than 1 % of the critical rate to keep the intergalactic medium ionized at $z = 7$, and thus indicates that quasars are not a major contributor to cosmic reionization., Comment: The Astrophysical Journal Letters, in press

We theoretically investigate a Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) type superfluid phase transition in a driven-dissipative two-component Fermi gas. The system is assumed to be in the non-equilibrium steady state, which is tuned by adjusting the chemical potential difference between two reservoirs that are coupled with the system. Including pairing fluctuations by extending the strong-coupling theory developed in the thermal-equilibrium state by Nozieres and Schmitt-Rink to this non-equilibrium case, we show that a non-equilibrium FFLO (NFFLO) phase transition can be realized without spin imbalance, under the conditions that (1) the two reservoirs imprint a two-edge structure on the momentum distribution of Fermi atoms, and (2) the system is loaded on a three-dimensional cubic optical lattice. While the two edges work like two Fermi surfaces with different sizes, the role of the optical lattice is to prevent the NFFLO long-range order from destruction by NFFLO pairing fluctuations. We also draw the non-equilibrium mean-field phase diagram in terms of the chemical potential difference between the two reservoirs, a fictitious magnetic field to tune the spin imbalance of the system, and the environmental temperature of the reservoirs, to clarify the relation between the NFFLO state and the ordinary thermal-equilibrium FFLO state discussed in spin-imbalanced Fermi gases., Comment: 20 pages, 15 figures

Modern air vehicles perform a wide range of operations, including transportation, defense, surveillance, and rescue. These aircraft can fly in calm conditions but avoid operations in gusty environments, encountered in urban canyons, over mountainous terrains, and in ship wakes. With extreme weather becoming ever more frequent due to global warming, it is anticipated that aircraft, especially those that are smaller in size, will encounter sizeable atmospheric disturbances and still be expected to achieve stable flight. However, there exists virtually no theoretical fluid-dynamic foundation to describe the influence of extreme vortical gusts on wings. To compound this difficulty, there is a large parameter space for gust-wing interactions. While such interactions are seemingly complex and different for each combination of gust parameters, we show that the fundamental physics behind extreme aerodynamics is far simpler and lower-rank than traditionally expected. We reveal that the nonlinear vortical flow field over time and parameter space can be compressed to only three variables with a lift-augmented autoencoder while holding the essence of the original high-dimensional physics. Extreme aerodynamic flows can be compressed through machine learning into a low-dimensional manifold, which can enable real-time sparse reconstruction, dynamical modeling, and control of extremely unsteady gusty flows. The present findings offer support for the stable flight of next-generation small air vehicles in atmosphere conditions traditionally considered unflyable.

Reconstruction of unsteady vortical flow fields from limited sensor measurements is challenging. We develop machine learning methods to reconstruct flow features from sparse sensor measurements during transient vortex-airfoil wake interaction using only a limited amount of training data. The present machine learning models accurately reconstruct the aerodynamic force coefficients, pressure distributions over airfoil surface, and two-dimensional vorticity field for a variety of untrained cases. Multi-layer perceptron is used for estimating aerodynamic forces and pressure profiles over the surface, establishing a nonlinear model between the pressure sensor measurements and the output variables. A combination of multi-layer perceptron with convolutional neural network is utilized to reconstruct the vortical wake. Furthermore, the use of transfer learning and long short-term memory algorithm combined in the training models greatly improves the reconstruction of transient wakes by embedding the dynamics. The present machine-learning methods are able to estimate the transient flow features while exhibiting robustness against noisy sensor measurements. Finally, appropriate sensor locations over different time periods are assessed for accurately estimating the wakes. The present study offers insights into the dynamics of vortex-airfoil interaction and the development of data-driven flow estimation., Comment: To appear in Theoretical and Computational Fluid Dynamics