Photonic Quantum Metrology

Quantum Metrology is one of the most promising application of quantum technologies. The aim of this research field is the estimation of unknown parameters exploiting quantum resources, whose application can lead to enhanced performances with respect to classical strategies. Several physical quantum systems can be employed to develop quantum sensors, and photonic systems represent ideal probes for a large number of metrological tasks. Here we review the basic concepts behind quantum metrology and then focus on the application of photonic technology for this task, with particular attention to phase estimation. We describe the current state of the art in the field in terms of platforms and quantum resources. Furthermore, we present the research area of multiparameter quantum metrology, where multiple parameters have to be estimated at the same time. We conclude by discussing the current experimental and theoretical challenges, and the open questions towards implementation of photonic quantum sensors with quantum-enhanced performances in the presence of noise.Comment: 51 pages, 9 figures, 967 references. Comments and feedbacks are very welcom

Entanglement-Assisted Absorption Spectroscopy

Spectroscopy is an important tool for probing the properties of materials, chemicals and biological samples. We design a practical transmitter-receiver system that exploits entanglement to achieve a provable quantum advantage over all spectroscopic schemes based on classical sources. To probe the absorption spectra, modelled as pattern of transmissivities among different frequency modes, we employ broad-band signal-idler pairs in two-mode squeezed vacuum states. At the receiver side, we apply photodetection after optical parametric amplification. Finally, we perform a maximal-likehihood decision test on the measurement results, achieving orders-of-magnitude-lower error probability than the optimum classical systems in various examples, including `wine-tasting' and `drug-testing' where real molecules are considered. In detecting the presence of an absorption line, our quantum scheme achieves the optimum performance allowed by quantum mechanics. The quantum advantage in our system is robust against noise and loss, which makes near-term experimental demonstration possible

New Concepts in Quantum Metrology: Dynamics, Machine Learning, and Bounds on Measurement Precision

Diese kumulative Promotionsarbeit befasst sich mit theoretischer Quantenmetrologie, der Theorie von Messung und Schätzung unter Zuhilfenahme von Quantenressourcen. Viele Vorschläge für quantenverbesserte Sensoren beruhen auf der Präparation von nichtklassischen Anfangszuständen und integrabler Dynamik. Allerdings sind solche nichtklassischen Zustände schwierig zu präparieren und gegen Dekohärenz zu schützen. Alternativ schlagen wir in dieser Promotionsarbeit sogenannte quantenchaotische Sensoren vor, die auf klassischen Anfangszuständen beruhen, die einfach zu präparieren sind, wobei Quantenverbesserungen an der Dynamik vorgenommen werden. Diese Herangehensweise hat ihren Ursprung darin, dass sowohl Quantenchaos als auch Quantenmetrologie über die Empfindlichkeit für kleine Änderungen in der Dynamik charakterisiert werden. Wir erforschen unterschiedliche Arten von Dynamik am Beispiel des Modells eines gestoßenen Quantenkreisels ("kicked top"), dessen Dynamik durch nichtlineare Kontrollpulse quantenchaotisch wird. Außerdem zeigen wir, dass Quantenchaos in der Lage ist, schädlichen Dekohärenzeffekte abzuschwächen. Insbesondere präsentieren wir einen Vorschlag für ein quantenchaotisches Cäsiumdampf-Magnetometer. Mit der Hilfe von Bestärkendem Lernen verbessern wir Zeitpunkt und Stärke der nichtlinearen Pulse im Modell des gestoßenen Quantenkreisels mit Superradianzdämpfung. Für diesen Fall finden wir, dass die Kontrollstrategie als eine dynamische Form der Spin-Quetschung verstanden werden kann. Ein anderer Teil dieser Promotionsarbeit beschäftigt sich mit bayesscher Quantenschätzung und insbesondere mit dem Problem der heuristischen Gestaltung von Experimenten. Wir trainieren neuronale Netze mit einer Kombination aus überwachtem und bestärkendem Lernen, um diese zu schnellen und starken Heuristiken für die Gestaltung von Experimenten zu machen. Die Vielseitigkeit unserer Methode zeigen wir anhand von Beispielen zu Einzel- und Mehrparameterschätzung, in denen die trainierten neuronalen Netze die Leistung der modernsten Heuristiken übertreffen. Außerdem beschäftigen wir uns mit einer lange unbewiesenen Vermutung aus dem Bereich der Quantenmetrologie: Wir liefern einen Beweis für diese Vermutung und finden einen Ausdruck für die maximale Quantenfischerinformation für beliebige gemischte Zustände und beliebige unitäre Dynamik, finden Bedingungen für optimale Zustandspräparation und optimale dynamische Kontrolle, und verwenden diese Ergebnisse, um zu beweisen, dass die Heisenberg-Schranke sogar mit thermischen Zuständen beliebiger (endlicher) Temperatur erreicht werden kann.This cumulative thesis is concerned with theoretical quantum metrology, the theory of measurement and estimation using quantum resources. Possible applications of quantum-enhanced sensors include the measurement of magnetic fields, gravitational wave detection, navigation, remote sensing, or the improvement of frequency standards. Many proposals for quantum-enhanced sensors rely on the preparation of non-classical initial states and integrable dynamics. However, such non-classical states are generally difficult to prepare and to protect against decoherence. As an alternative, in this thesis, we propose so-called quantum-chaotic sensors which make use of classical initial states that are easy to prepare while quantum enhancements are applied to the dynamics. This approach is motivated by the insight that quantum chaos and quantum metrology are both characterized by the sensitivity to small changes of the dynamics. At the example of the quantum kicked top model, where nonlinear control pulses render the dynamics quantum-chaotic, we explore different dynamical regimes for quantum sensors. Further, we demonstrate that quantum chaos is able to alleviate the detrimental effects of decoherence. In particular, we present a proposal for a quantum-chaotic cesium-vapor magnetometer. With the help of reinforcement learning, we further optimize timing and strength of the nonlinear control pulses for the kicked top model with superradiant damping. In this case, the optimized control policy is identified as a dynamical form of spin squeezing. Another part of this thesis deals with Bayesian quantum estimation and, in particular, with the problem of experiment design heuristics. We train neural networks with a combination of supervised and reinforcement learning to become fast and strong experiment design heuristics. We demonstrate the versatility of this method using examples of single and multi-parameter estimation where the trained neural networks surpass the performance of well-established heuristics. Finally, this thesis deals with a long-time outstanding conjecture in quantum metrology: we prove this conjecture and find an expression for the maximal quantum Fisher information for any mixed initial state and any unitary dynamics, provide conditions for optimal state preparation and optimal control of the dynamics, and utilize these results to prove that Heisenberg scaling can be achieved even with thermal states of arbitrary (finite) temperature

Optimal control for Hamiltonian parameter estimation in non-commuting and bipartite quantum dynamics

The ability to characterise a Hamiltonian with high precision is crucial for the implementation of quantum technologies. In addition to the well-developed approaches utilising optimal probe states and optimal measurements, the method of optimal control can be used to identify time-dependent pulses applied to the system to achieve higher precision in the estimation of Hamiltonian parameters, especially in the presence of noise. Here, we extend optimally controlled estimation schemes for single qubits to non-commuting dynamics as well as two interacting qubits, demonstrating improvements in terms of maximal precision, time-stability, as well as robustness over uncontrolled protocols.Comment: Submission to SciPost Physics; 18 pages, 13 figure

The Boston University Photonics Center annual report 2015-2016

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2015-2016 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This has been a good year for the Photonics Center. In the following pages, you will see that this year the Center’s faculty received prodigious honors and awards, generated more than 100 notable scholarly publications in the leading journals in our field, and attracted $18.9M in new research grants/contracts. Faculty and staff also expanded their efforts in education and training, and cooperated in supporting National Science Foundation sponsored Sites for Research Experiences for Undergraduates and for Research Experiences for Teachers. As a community, we emphasized the theme of “Frontiers in Plasmonics as Enabling Science in Photonics and Beyond” at our annual symposium, hosted by Bjoern Reinhard. We continued to support the National Photonics Initiative, and contributed as a cooperating site in the American Institute for Manufacturing Integrated Photonics (AIM Photonics) which began this year as a new photonics-themed node in the National Network of Manufacturing Institutes. Highlights of our research achievements for the year include an ambitious new DoD-sponsored grant for Development of Less Toxic Treatment Strategies for Metastatic and Drug Resistant Breast Cancer Using Noninvasive Optical Monitoring led by Professor Darren Roblyer, continued support of our NIH-sponsored, Center for Innovation in Point of Care Technologies for the Future of Cancer Care led by Professor Cathy Klapperich, and an exciting confluence of new grant awards in the area of Neurophotonics led by Professors Christopher Gabel, Timothy Gardner, Xue Han, Jerome Mertz, Siddharth Ramachandran, Jason Ritt, and John White. Neurophotonics is fast becoming a leading area of strength of the Photonics Center. The Industry/University Collaborative Research Center, which has become the centerpiece of our translational biophotonics program, continues to focus onadvancing the health care and medical device industries, and has entered its sixth year of operation with a strong record of achievement and with the support of an enthusiastic industrial membership base

Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe

Quantum optimal control, a toolbox for devising and implementing the shapes of external fields that accomplish given tasks in the operation of a quantum device in the best way possible, has evolved into one of the cornerstones for enabling quantum technologies. The last few years have seen a rapid evolution and expansion of the field. We review here recent progress in our understanding of the controllability of open quantum systems and in the development and application of quantum control techniques to quantum technologies. We also address key challenges and sketch a roadmap for future developments.Comment: this is a living document - we welcome feedback and discussio