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William R. Clements

Other affiliations: Peking University
Bio: William R. Clements is an academic researcher from University of Oxford. The author has contributed to research in topics: Beam splitter & Raman spectroscopy. The author has an hindex of 17, co-authored 37 publications receiving 1519 citations. Previous affiliations of William R. Clements include Peking University.

Papers
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Journal ArticleDOI
20 Dec 2016
TL;DR: In this article, an alternative arrangement of beam splitters and phase shifters was proposed for universal multiport interferometers, which requires half the optical depth of the Reck et al. design and is significantly more robust to optical losses.
Abstract: Universal multiport interferometers, which can be programmed to implement any linear transformation between multiple channels, are emerging as a powerful tool for both classical and quantum photonics. These interferometers are typically composed of a regular mesh of beam splitters and phase shifters, allowing for straightforward fabrication using integrated photonic architectures and ready scalability. The current, standard design for universal multiport interferometers is based on work by Reck et al. [Phys. Rev. Lett.73, 58 (1994)PRLTAO0031-900710.1103/PhysRevLett.73.58]. We demonstrate a new design for universal multiport interferometers based on an alternative arrangement of beam splitters and phase shifters, which outperforms that by Reck et al. Our design requires half the optical depth of the Reck design and is significantly more robust to optical losses.

572 citations

Posted Content
TL;DR: In this paper, an alternative arrangement of beam splitters and phase shifters was proposed for universal multiport interferometers, which was shown to be more robust to optical losses.
Abstract: Universal multiport interferometers, which can be programmed to implement any linear transformation between multiple channels, are emerging as a powerful tool for both classical and quantum photonics. These interferometers are typically composed of a regular mesh of beam splitters and phase shifters, allowing for straightforward fabrication using integrated photonic architectures and ready scalability. The current, standard design for universal multiport interferometers is based on work by Reck et al (Phys. Rev. Lett. 73, 58, 1994). We demonstrate a new design for universal multiport interferometers based on an alternative arrangement of beam splitters and phase shifters, which outperforms that by Reck et al. Our design occupies half the physical footprint of the Reck design and is significantly more robust to optical losses.

396 citations

Journal ArticleDOI
TL;DR: A new label-free sensing mechanism is demonstrated experimentally by monitoring the whispering-gallery mode broadening in microcavities that is immune to both noise from the probe laser and environmental disturbances, and is able to remove the strict requirement for ultra-high-Q mode cavities for sensitive nanoparticle detection.
Abstract: A new label-free sensing mechanism is demonstrated experimentally by monitoring the whispering-gallery mode broadening in microcavities. It is immune to both noise from the probe laser and environmental disturbances, and is able to remove the strict requirement for ultra-high-Q mode cavities for sensitive nanoparticle detection. This ability to sense nanoscale objects and biological analytes is particularly crucial for wide applications.

245 citations

Journal ArticleDOI
TL;DR: This work reports for the first time, to their knowledge, single nanoparticle detection by monitoring the beat frequency of split-mode Raman lasers in high-Q optical microcavities in both air and an aqueous environment, with an ultralow detection limit.
Abstract: Ultrasensitive nanoparticle detection holds great potential for early-stage diagnosis of human diseases and for environmental monitoring. In this work, we report for the first time, to our knowledge, single nanoparticle detection by monitoring the beat frequency of split-mode Raman lasers in high-Q optical microcavities. We first demonstrate this method by controllably transferring single 50-nm–radius nanoparticles to and from the cavity surface using a fiber taper. We then realize real-time detection of single nanoparticles in an aqueous environment, with a record low detection limit of 20 nm in radius, without using additional techniques for laser noise suppression. Because Raman scattering occurs in most materials under practically any pump wavelength, this Raman laser-based sensing method not only removes the need for doping the microcavity with a gain medium but also loosens the requirement of specific wavelength bands for the pump lasers, thus representing a significant step toward practical microlaser sensors.

234 citations

Journal ArticleDOI
03 Apr 2020
TL;DR: The approach of exploratory combinatorsial optimization (ECO-DQN) is, in principle, applicable to any combinatorial problem that can be defined on a graph and can be combined with other search methods to further improve performance, which is demonstrated using a simple random search.
Abstract: Many real-world problems can be reduced to combinatorial optimization on a graph, where the subset or ordering of vertices that maximize some objective function must be found. With such tasks often NP-hard and analytically intractable, reinforcement learning (RL) has shown promise as a framework with which efficient heuristic methods to tackle these problems can be learned. Previous works construct the solution subset incrementally, adding one element at a time, however, the irreversible nature of this approach prevents the agent from revising its earlier decisions, which may be necessary given the complexity of the optimization task. We instead propose that the agent should seek to continuously improve the solution by learning to explore at test time. Our approach of exploratory combinatorial optimization (ECO-DQN) is, in principle, applicable to any combinatorial problem that can be defined on a graph. Experimentally, we show our method to produce state-of-the-art RL performance on the Maximum Cut problem. Moreover, because ECO-DQN can start from any arbitrary configuration, it can be combined with other search methods to further improve performance, which we demonstrate using a simple random search.

102 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: This article reviews in a selective way the recent research on the interface between machine learning and the physical sciences, including conceptual developments in ML motivated by physical insights, applications of machine learning techniques to several domains in physics, and cross fertilization between the two fields.
Abstract: Machine learning (ML) encompasses a broad range of algorithms and modeling tools used for a vast array of data processing tasks, which has entered most scientific disciplines in recent years. This article reviews in a selective way the recent research on the interface between machine learning and the physical sciences. This includes conceptual developments in ML motivated by physical insights, applications of machine learning techniques to several domains in physics, and cross fertilization between the two fields. After giving a basic notion of machine learning methods and principles, examples are described of how statistical physics is used to understand methods in ML. This review then describes applications of ML methods in particle physics and cosmology, quantum many-body physics, quantum computing, and chemical and material physics. Research and development into novel computing architectures aimed at accelerating ML are also highlighted. Each of the sections describe recent successes as well as domain-specific methodology and challenges.

1,504 citations

Journal ArticleDOI
09 Aug 2017-Nature
TL;DR: An alternative sensing scheme is demonstrated, by which the sensitivity of microcavities can be enhanced when operated at non-Hermitian spectral degeneracies known as exceptional points, paves the way for sensors with unprecedented sensitivity.
Abstract: Sensors play an important part in many aspects of daily life such as infrared sensors in home security systems, particle sensors for environmental monitoring and motion sensors in mobile phones. High-quality optical microcavities are prime candidates for sensing applications because of their ability to enhance light-matter interactions in a very confined volume. Examples of such devices include mechanical transducers, magnetometers, single-particle absorption spectrometers, and microcavity sensors for sizing single particles and detecting nanometre-scale objects such as single nanoparticles and atomic ions. Traditionally, a very small perturbation near an optical microcavity introduces either a change in the linewidth or a frequency shift or splitting of a resonance that is proportional to the strength of the perturbation. Here we demonstrate an alternative sensing scheme, by which the sensitivity of microcavities can be enhanced when operated at non-Hermitian spectral degeneracies known as exceptional points. In our experiments, we use two nanoscale scatterers to tune a whispering-gallery-mode micro-toroid cavity, in which light propagates along a concave surface by continuous total internal reflection, in a precise and controlled manner to exceptional points. A target nanoscale object that subsequently enters the evanescent field of the cavity perturbs the system from its exceptional point, leading to frequency splitting. Owing to the complex-square-root topology near an exceptional point, this frequency splitting scales as the square root of the perturbation strength and is therefore larger (for sufficiently small perturbations) than the splitting observed in traditional non-exceptional-point sensing schemes. Our demonstration of exceptional-point-enhanced sensitivity paves the way for sensors with unprecedented sensitivity.

1,403 citations

Journal ArticleDOI
TL;DR: This review presents strategies employed to construct quantum algorithms for quantum chemistry, with the goal that quantum computers will eventually answer presently inaccessible questions, for example, in transition metal catalysis or important biochemical reactions.
Abstract: One of the most promising suggested applications of quantum computing is solving classically intractable chemistry problems. This may help to answer unresolved questions about phenomena such as high temperature superconductivity, solid-state physics, transition metal catalysis, and certain biochemical reactions. In turn, this increased understanding may help us to refine, and perhaps even one day design, new compounds of scientific and industrial importance. However, building a sufficiently large quantum computer will be a difficult scientific challenge. As a result, developments that enable these problems to be tackled with fewer quantum resources should be considered important. Driven by this potential utility, quantum computational chemistry is rapidly emerging as an interdisciplinary field requiring knowledge of both quantum computing and computational chemistry. This review provides a comprehensive introduction to both computational chemistry and quantum computing, bridging the current knowledge gap. Major developments in this area are reviewed, with a particular focus on near-term quantum computation. Illustrations of key methods are provided, explicitly demonstrating how to map chemical problems onto a quantum computer, and how to solve them. The review concludes with an outlook on this nascent field.

954 citations

Journal ArticleDOI
TL;DR: This Review provides an overview of the algorithms and results that are relevant for quantum chemistry and aims to help quantum chemists who seek to learn more about quantum computing and quantum computing researchers who would like to explore applications in quantum chemistry.
Abstract: Practical challenges in simulating quantum systems on classical computers have been widely recognized in the quantum physics and quantum chemistry communities over the past century. Although many approximation methods have been introduced, the complexity of quantum mechanics remains hard to appease. The advent of quantum computation brings new pathways to navigate this challenging and complex landscape. By manipulating quantum states of matter and taking advantage of their unique features such as superposition and entanglement, quantum computers promise to efficiently deliver accurate results for many important problems in quantum chemistry, such as the electronic structure of molecules. In the past two decades, significant advances have been made in developing algorithms and physical hardware for quantum computing, heralding a revolution in simulation of quantum systems. This Review provides an overview of the algorithms and results that are relevant for quantum chemistry. The intended audience is both quantum chemists who seek to learn more about quantum computing and quantum computing researchers who would like to explore applications in quantum chemistry.

910 citations