11 research outputs found
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Quantum Communications with Near-Term Quantum Networks
No full textQuantum networks promise to enable provably secure communications, enhanced sensing, enhanced imaging and distributed quantum information processing. However, low generation rates and the quality of distributed entanglement will constrain near-term quantum networks. This dissertation explores near-term quantum networks for shared entanglement generation. We begin by reviewing the theoretical limits of quantum communications and the principles underlying quantum links and repeaters, including various photon-based and memory qubit encodings. We then analyze quantum link architectures for entanglement generation for a diverse class of photonic encodings. We subsequently analyze linear-chain quantum repeater networks; we discuss improvements to the rate-vs.-loss scaling with time-multiplexed entanglement swaps and the practical limitations associated with finite memory coherence times and buffer capacities. We propose satellite-assisted quantum links as an alternative to quantum repeaters, presenting and analyzing several candidate link architectures
Entangling Quantum Memories via Heralded Photonic Bell Measurement
No full textA common way to entangle quantum memories is via photonic entanglement swaps.
Each of two memories, connected by an optical channel, emits a photonic qubit
entangled with itself, and the photonic qubits undergo an entanglement swap on
a beamsplitter in the middle of the channel. We compare two choices of encoding
of the photonic qubit: single rail and dual rail. At low channel loss the
dual-rail scheme outperforms the single rail scheme. However, as expected, the
high-loss rate asymptote for the dual rail scheme scales quadratically worse
with loss compared with single rail. Considering the following non-idealities:
imperfect mode matching at the swap, carrier-phase mismatch across the
interfered photonic qubits, and detector excess noise, we evaluate the density
operator of the heralded two-qubit entangled state. We calculate a lower bound
on its distillable entanglement per copy, and its Fidelity (with the ideal Bell
state). For both schemes, imperfect swap-visibility results in a
constant-factor decrease in the rate, while excess noise results in a dropoff
of distillable entanglement beyond a certain total channel loss threshold, to
zero. Despite the single-rail scheme's better rate-loss scaling, it is more
severely affected by excess noise. The single-rail scheme is adversely affected
by stochastic carrier-phase mismatch, which does not affect the dual-rail
scheme. We study entanglement distillation on the heralded noisy entangled
states for both methods, and outline a suite of quantum networking studies that
our work could incite.Comment: 8 pages and 9 figures (main text); 4 appendices with 8 figures;
Comments are welcome
To Tune or not to Tune: Hyperparameter Influence on the Learning Curve
No full textA learning curve displays the measure of accuracy/error on test data of a machine learning algorithm trained on different amounts of training data. They can be modeled by parametric curve models that help predict accuracy improvement through curve extrapolation methods. However, these learning curves have only been mainly generated from default learning algorithms. Research into tuning the machine learning algorithm and its effect on the learning curve has not been adequately researched. This research aims to look at the influence of hyperparameter tuning on the learning curve. This regards not only how the learning curve shape changes in general but also how different parametric models are affected when a learner undergoes tuning. We experiment with the decision tree and KNeighbors classifier which undergo significant hyperparameter tuning. We find that the tuned learner performs marginally better than the default learner for anchors past 25\% of the data for the majority of the tested datasets. We also observe that the tuned learner displays a smoothing behaviour that makes ill-behaved curves more well-behaved. In terms of the curve fitting, the tuned learners do not uncover any curve models nor does it show any statistical significance, and instead performs very similarly to the default learners. CSE3000 Research ProjectComputer Science and Engineerin
Exploring the possibility of a complex-valued non-Gaussianity measure for quantum states of light
No full textWe consider a quantity that is the differential relative entropy between a generic Wigner function and a Gaussian one. We prove that said quantity is minimized with respect to its Gaussian argument, if both Wigner functions in the argument of the Wigner differential entropy have the same first and second moments, i.e., if the Gaussian argument is the Gaussian associate of the other, generic Wigner function. Therefore, we introduce the differential relative entropy between any Wigner function and its Gaussian associate and we examine its potential as a non-Gaussianity measure. We prove that said quantity is faithful, invariant under Gaussian unitary operations, and find a sufficient condition on its monotonic behavior under Gaussian channels. We provide numerical results supporting aforesaid condition. The proposed, phase-space based non-Gaussianity measure is complex-valued, with its imaginary part possessing the physical meaning of the negative volume of the Wigner function. At the same time, the real part of this measure provides an extra layer of information, rendering the complex-valued quantity a measure of non-Gaussianity, instead of a quantity pertaining only to the negativity of the Wigner function. We examine the usefulness of our measure to non-Gaussian quantum state engineering with partial measurements
Optimal Entanglement Distribution using Satellite Based Quantum Networks
No full textRecent technological advancements in satellite based quantum communication
has made it a promising technology for realizing global scale quantum networks.
Due to better loss distance scaling compared to ground based fiber
communication, satellite quantum communication can distribute high quality
quantum entanglements among ground stations that are geographically separated
at very long distances. This work focuses on optimal distribution of bipartite
entanglements to a set of pair of ground stations using a constellation of
orbiting satellites. In particular, we characterize the optimal
satellite-to-ground station transmission scheduling policy with respect to the
aggregate entanglement distribution rate subject to various resource
constraints at the satellites and ground stations. We cast the optimal
transmission scheduling problem as an integer linear programming problem and
solve it efficiently for some specific scenarios. Our framework can also be
used as a benchmark tool to measure the performance of other potential
transmission scheduling policies
Coherent manipulation of graph states composed of finite-energy Gottesman-Kitaev-Preskill-encoded qubits
No full textGraph states are a central resource in measurement-based quantum information
processing. In the photonic qubit architecture based on
Gottesman-Kitaev-Preskill (GKP) encoding, the generation of high-fidelity graph
states composed of realistic, finite-energy approximate GKP-encoded qubits thus
constitutes a key task. We consider the finite-energy approximation of GKP
qubit states given by a coherent superposition of shifted finite-squeezed
vacuum states, where the displacements are Gaussian distributed. We present an
exact description of graph states composed of such approximate GKP qubits as a
coherent superposition of a Gaussian ensemble of randomly displaced ideal
GKP-qubit graph states. We determine the transformation rules for the
covariance matrix and the mean displacement vector of the Gaussian distribution
of the ensemble under tools such as GKP-Steane error correction and fusion
operations that can be used to grow large, high-fidelity GKP-qubit graph
states. The former captures the noise in the graph state due to the
finite-energy approximation of GKP qubits, while the latter relates to the
possible absolute displacement errors on the individual qubits due to the
homodyne measurements that are a part of these tools. The rules thus help in
pinning down an exact coherent error model for graph states generated from
truly finite-energy GKP qubits, which can shed light on their error correction
properties.Comment: 17 pages. Comments are welcom
Blockwise Key Distillation in Satellite-based Quantum Key Distribution
No full textFree-space satellite communication has significantly lower photon loss than
terrestrial communication via optical fibers. Satellite-based quantum key
distribution (QKD) leverages this advantage and provides a promising direction
in achieving long-distance inter-continental QKD. Satellite channels, however,
can be highly dynamic due to various environmental factors and time-of-the-day
effects, leading to heterogeneous noises over time. In this paper, we compare
two key distillation techniques for satellite-based QKD. One is the traditional
{\em non-blockwise} strategy that treats all the signals as a whole; the other
is a {\em blockwise} strategy that divides the signals into individual blocks
that have similar noise characteristics and processes them independently.
Through extensive simulation in a wide range of settings, we show trends in
optimal parameter choices and when one strategy provides better key generation
rates than the other. Our results show that the blockwise strategy can lead to
up to key rate improvement (leading to on average more
key bits per day) when considering two types of blocks, i.e., for nighttime and
daytime, respectively. The blockwise strategy only requires changes in the
classical post-processing stage of QKD and can be easily deployed in existing
satellite systems
Mobipedia: Mobile Applications Linked Data
No full text14th International Semantic Web Conference (ISWC 2015), October 2015We present Mobipedia, an integrated knowledge base with
information about 1 million mobile applications (apps) such as their category, meta-data (author, reviews, rating, release date), permissions and
libraries used, and similar apps. The goal of Mobipedia is to integrate
unstructured and semi-structured data about mobile apps from publicly
available data sources and publish it as Linked Data using RDF. We describe the extraction process for facts, access mechanisms to the knowledge base, and an overview of applications facilitated by Mobipedia.This research work has been supported by RADICLE project
CNS-1059436, CNS-1212943, CNS-1118127 and CNS-1450768, CICYT project TIN2013-
46238-C4-4-R and DGA FSE, U.S. National Science Foundation awards 0910838 and
1228198.https://robertoyus.com/publication/iswc2-2015
Zero-Added-Loss Entangled-Photon Multiplexing for Ground- and Space-Based Quantum Networks
No full textWe propose a scheme for optical entanglement distribution in quantum networks based on a quasideterministic entangled photon-pair source. By combining heralded photonic Bell-pair generation with spectral mode conversion to interface with quantum memories, the scheme eliminates switching losses due to multiplexing in the source. We analyze this "zero-added-loss multiplexing"(ZALM) Bell-pair source for the particularly challenging problem of long-baseline entanglement distribution via satellites and ground-based memories, where it unlocks additional advantages: (i) the substantially higher channel efficiency η of downlinks versus uplinks with realistic adaptive optics, and (ii) photon loss occurring before interaction with the quantum memory - i.e., Alice and Bob receiving rather than transmitting - improve entanglement generation rate scaling by O(η). Based on numerical analyses, we estimate our protocol to achieve >10ebit/s at memory multiplexing of 102 spin qubits for ground distance >102km, with the spin-spin Bell-state fidelity exceeding 99%. Our architecture presents a blueprint for realizing global-scale quantum networks in the near term.</p
Fintech founders: inspiring tales from the entrepreneurs that are changing finance/ Agustín Rubini.
No full textIncludes index.In English."Over 70 in-depth interviews of Fintech Founders provide lessons from some of the most successful fintech entrepreneurs that will help you understand the challenges and opportunities of applying technology and collaboration to solve some key problems of the financial services industry. This book is for entrepreneurs, for people working inside of large organizations and everyone in between who is interested to learn the secrets of successful entrepreneurs. In this advice-filled resource, Rubini gathers advice that comes from a diverse range of financial services niches including financing, banking, payments, wealth management, insurance, and cryptocurrencies, to help you harness the insights of thought leaders. Those working inside the financial services industry and those interested in working in or starting up businesses in financial services will learn valuable lessons on how to take an idea forward, how to find the right business founders, how to seek funding, how to learn from initial mistakes, and how to define and reposition your business model. Rubini also inquires into the future of fintech and uncovers provoking and insightful predictions."--Frontmatter -- About the Author -- Foreword -- Contents -- Preface -- Part 1: Financing Fintechs -- Introduction -- Chapter 1. Henrique Dubugras -- Chapter 2. Renaud Laplanche -- Chapter 3. Levi King -- Chapter 4. Sam Graziano -- Chapter 5. Michael Garrity, Paul Sehr, Casper Wong -- Chapter 6. Sergio Furio -- Chapter 7. Alejandro Cosentino -- Chapter 8. Christoph Rieche -- Chapter 9. Conrad Ford -- Chapter 10. Gamal Moukabary -- Chapter 11. Geetansh Bamania -- Chapter 12. Kelvin Teo -- Chapter 13. Harshvardhan Lunia -- Chapter 14. Simon Loong -- Part 2: Banking and Savings Fintechs -- Introduction -- Chapter 15. Anthony Thomson -- Chapter 16. Nick Ogden -- Chapter 17. Norris Koppel -- Chapter 18. Ricky Knox -- Chapter 19. Mutaz Qubbaj -- Chapter 20. Matthias Kröner -- Chapter 21. Tamaz Georgadze -- Chapter 22. Dr. Yassin Hankir -- Chapter 23. Brett King -- Chapter 24. Pierpaolo Barbieri -- Part 3: Payments Fintechs -- Introduction -- Chapter 25. Mike Massaro -- Chapter 26. Patrick Postrehovsky -- Chapter 27. Sami Louali -- Chapter 28. Elizabeth Rossiello -- Chapter 29. Brett Meyers -- Chapter 30. Christo Georgiev -- Chapter 31. Jacob de Geer -- Chapter 32. Arpit Gupta -- Chapter 33. Wong Joo Seng -- Chapter 34. Prajit Nanu -- Part 4: SME-Specific Fintechs -- Introduction -- Chapter 35. Gert Sylvest -- Chapter 36. Gordon Trouncer Downes -- Chapter 37. Sebastián Cadenas -- Chapter 38. Joel Perlman -- Chapter 39. Tim Fouracre -- Chapter 40. Nicolas Reboud, Raphaël Simon -- Chapter 41. Johan Lorenzen -- Chapter 42. Sean Yu -- Part 5: Investment Fintechs -- Introduction -- Chapter 43. Aaron Klein -- Chapter 44. Mazy Dar -- Chapter 45. John Fawcett -- Chapter 46. Facundo Garreton -- Chapter 47. Gonçalo de Vasconcelos -- Chapter 48. Yoni Assia -- Chapter 49. Adam Leonard -- Chapter 50. Barry Freeman -- Chapter 51. Mike Kayamori -- Part 6: Insurance Fintechs -- Introduction -- Chapter 52. Karn Saroya -- Chapter 53. Tim Attia -- Chapter 54. Michael Serbinis -- Chapter 55. Barry McCarthy -- Chapter 56. Dr. Christopher Oster -- Chapter 57. Talal Bayaa -- Chapter 58. Gustaf Agartson -- Part 7: Data and Analytics Fintechs -- Introduction -- Chapter 59. Stephane Dubois -- Chapter 60. Zor Gorelov -- Chapter 61. Gunnar Carlsson and Gurjeet Singh -- Chapter 62. Walter Alini, Daniel Moisset, Javier Mansilla, Juan Chacon -- Chapter 63. Steve Kirsch and Marten Nelson -- Chapter 64 .Matthew Hodgson -- Chapter 65. Jonathan Epstein -- Part 8: Support Fintechs -- Introduction -- Chapter 66. Steve Polsky -- Chapter 67. Stephen Ufford -- Chapter 68. Sebastian Stranieri -- Chapter 69. Niall Twomey -- Chapter 70. Owen Hall and Vikas Tripathi -- Chapter 71. Bill Safran -- Chapter 72. Raz Abramov -- Chapter 73. William Wei -- Join our newsletter -- Index1 online resource (XVIII, 579 pages)
