442 research outputs found
A Quantum Federated Learning Framework for Classical Clients
Quantum Federated Learning (QFL) enables collaborative training of a Quantum
Machine Learning (QML) model among multiple clients possessing quantum
computing capabilities, without the need to share their respective local data.
However, the limited availability of quantum computing resources poses a
challenge for each client to acquire quantum computing capabilities. This
raises a natural question: Can quantum computing capabilities be deployed on
the server instead? In this paper, we propose a QFL framework specifically
designed for classical clients, referred to as CC-QFL, in response to this
question. In each iteration, the collaborative training of the QML model is
assisted by the shadow tomography technique, eliminating the need for quantum
computing capabilities of clients. Specifically, the server constructs a
classical representation of the QML model and transmits it to the clients. The
clients encode their local data onto observables and use this classical
representation to calculate local gradients. These local gradients are then
utilized to update the parameters of the QML model. We evaluate the
effectiveness of our framework through extensive numerical simulations using
handwritten digit images from the MNIST dataset. Our framework provides
valuable insights into QFL, particularly in scenarios where quantum computing
resources are scarce
Trainability Analysis of Quantum Optimization Algorithms from a Bayesian Lens
The Quantum Approximate Optimization Algorithm (QAOA) is an extensively
studied variational quantum algorithm utilized for solving optimization
problems on near-term quantum devices. A significant focus is placed on
determining the effectiveness of training the -qubit QAOA circuit, i.e.,
whether the optimization error can converge to a constant level as the number
of optimization iterations scales polynomially with the number of qubits. In
realistic scenarios, the landscape of the corresponding QAOA objective function
is generally non-convex and contains numerous local optima. In this work,
motivated by the favorable performance of Bayesian optimization in handling
non-convex functions, we theoretically investigate the trainability of the QAOA
circuit through the lens of the Bayesian approach. This lens considers the
corresponding QAOA objective function as a sample drawn from a specific
Gaussian process. Specifically, we focus on two scenarios: the noiseless QAOA
circuit and the noisy QAOA circuit subjected to local Pauli channels. Our first
result demonstrates that the noiseless QAOA circuit with a depth of
can be trained efficiently,
based on the widely accepted assumption that either the left or right slice of
each block in the circuit forms a local 1-design. Furthermore, we show that if
each quantum gate is affected by a -strength local Pauli channel with the
noise strength range of to 0.1, the noisy QAOA circuit with
a depth of can also be trained
efficiently. Our results offer valuable insights into the theoretical
performance of quantum optimization algorithms in the noisy intermediate-scale
quantum era
Continuous fabrication of microcapsules with controllable metal covered nanoparticle arrays using droplet microfluidics for localized surface plasmon resonance
Particle-laden plasmonic microcapsules were fabricated continuously using microfluidic technology, showing high LSPR with high-density “hot-spot” scattering sites.</p
Orbital-angular-momentum fluorescence emission based on photon–electron interaction in a vortex field of an active optical fiber
We develop a model of interaction between photons and electrons in an active vortex field, which can generate a fluorescence spectrum with the characteristics of orbital angular momentum (OAM). In an active optical fiber, our findings generalize the notion of photon–electron interaction and point to a new kind of OAM-mode broad-spectrum light source, which could be interpreted in two processes: one microscopically is the excitation of OAM-carrying photons based on the photon–electron interaction; the other macroscopically is the emission and transmission of a donut-shaped fluorescence in a vortex field with a spiral phase wavefront in a ring-core active fiber. Here we present a straightforward experimental method that the emission of broad-spectrum fluorescence with an OAM feature is actualized and validated in a ring-core erbium-doped fiber. The spectrum has a broad spectral width up to 50 nm. Furthermore, four wavelengths are extracted from the fluorescence spectrum and superimposed with their corresponding Gaussian beams, from which the spiral-shaped interferograms of OAM modes in a broad spectrum are identified with high purity. The application of the OAM-based fluorescence light source may range from classical to quantum information technologies, and enable high-capacity communication, high-sensitivity sensing, high-resolution fluorescence imaging, etc
Association between sleep duration and quality with rapid kidney function decline and development of chronic kidney diseases in adults with normal kidney function: The China health and retirement longitudinal study
Research have shown that sleep is associated with renal function. However, the potential effects of sleep duration or quality on kidney function in middle-aged and older Chinese adults with normal kidney function has rarely been studied. Our study aimed to investigate the association of sleep and kidney function in middle-aged and older Chinese adults. Four thousand and eighty six participants with an eGFR ≥60 ml/min/1.73 m2 at baseline were enrolled between 2011 and 2015 from the China Health and Retirement Longitudinal Study. Survey questionnaire data were collected from conducted interviews in the 2011. The eGFR was estimated from serum creatinine and/or cystatin C using the Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPI). The primary outcome was defined as rapid kidney function decline. Secondary outcome was defined as rapid kidney function decline with clinical eGFR of <60 ml/min/1.73 m2 at the exit visit. The associations between sleep duration, sleep quality and renal function decline or chronic kidney disease (CKD) were assessed based with logistic regression model. Our results showed that 244 (6.0%) participants developed rapid decline in kidney function, while 102 (2.5%) developed CKD. In addition, participants who had 3–7 days of poor sleep quality per week had higher risks of CKD development (OR 1.86, 95% CI 1.24–2.80). However, compared with those who had 6–8 h of night-time sleep, no significantly higher risks of rapid decline in kidney function was found among those who had <6 h or >8 h of night time sleep after adjustments for demographic, clinical, or psychosocial covariates. Furthermore, daytime nap did not present significant risk in both rapid eGFR decline or CKD development. In conclusion, sleep quality was significantly associated with the development of CKD in middle-aged and older Chinese adults with normal kidney function
Ion Selectivity and Stability Enhancement of SPEEK/Lignin Membrane for Vanadium Redox Flow Battery: The Degree of Sulfonation Effect
A membrane of high ion selectivity, high stability, and low cost is desirable for vanadium redox flow battery (VRB). In this study, a composite membrane is formed by blending the sulfonated poly (ether ether ketone) with lignin (SPEEK/lignin), and optimized by tailoring the degree of sulfonation. The incorporation of lignin into the SPEEK matrix provides more proton transport pathway and meanwhile adjusts the water channel to repulse vanadium ions. The VRB cells assembled with the composite membranes exhibit high coulombic efficiency (~99.27%) and impressive energy efficiency (~82.75%). The cells maintain a discharge capacity of ~95% after 100 cycles and ~85% after 200 cycles at 120 mA cm−2, much higher than the commercial Nafion 212. The SPEEK/lignin composite membranes are promising for application in VRB system
The Problems of Civil Law in China and Japan
千葉大学大学院人文社会科学研究科研究プロジェクト報告書第171集『中日における民法現代化の課題』 小賀野晶一
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