Literature as Impossible

Panel: Writing as Philosophy and Craf

Modeling Scalability of Distributed Machine Learning

Present day machine learning is computationally intensive and processes large amounts of data. It is implemented in a distributed fashion in order to address these scalability issues. The work is parallelized across a number of computing nodes. It is usually hard to estimate in advance how many nodes to use for a particular workload. We propose a simple framework for estimating the scalability of distributed machine learning algorithms. We measure the scalability by means of the speedup an algorithm achieves with more nodes. We propose time complexity models for gradient descent and graphical model inference. We validate our models with experiments on deep learning training and belief propagation. This framework was used to study the scalability of machine learning algorithms in Apache Spark.Comment: 6 pages, 4 figures, appears at ICDE 201

Loss-tolerant quantum enhanced metrology and state engineering via the reverse Hong-Ou-Mandel effect

Preparing highly entangled quantum states between remote parties is a major challenge for quantum communications [1-8]. Particularly promising in this context are the N00N states, which are entangled N-photon wavepackets delocalized between two different locations, providing measurement sensitivity limited only by the uncertainty principle [1, 10-15]. However, these states are notoriously vulnerable to losses, making it difficult both to share them between remote locations, and to recombine them to exploit interference effects. Here we address this challenge by utilizing the reverse version of the Hong-Ou-Mandel effect [16] to prepare a high-fidelity two-photon N00N state shared between two parties connected by a lossy optical channel. Furthermore, we demonstrate that the enhanced phase sensitivity can be directly exploited in the two distant locations, and we remotely prepare superpositions of coherent states, known as Schr\"odinger's cat states" [17, 18]

Synthesis of the Einstein-Podolsky-Rosen entanglement in a sequence of two single-mode squeezers

Synthesis of the Einstein-Podolsky-Rosen entangled state --- the primary entangled resource in continuous-variable quantum-optical information processing --- is a technological challenge of great importance. Here we propose and implement a new scheme of generating this state. Two nonlinear optical crystals, positioned back-to-back in the waist of a pump beam, function as single-pass degenerate optical parametric amplifiers and produce single-mode squeezed vacuum states in orthogonal polarization modes, but in the same spatiotemporal mode. A subsequent pair of waveplates acts as a beam splitter, entangling the two polarization modes to generate the Einstein-Podolsky-Rosen state. This technique takes advantage of the strong nonlinearity associated with type-I phase-matching configuration while at the same time eliminating the need for actively stabilizing the optical phase between the two squeezers, which typically arises if these squeezers are spatially separated. We demonstrate our method in an experiment, preparing a 1.4 dB two-mode squeezed state and characterizing it via two-mode homodyne tomography.Comment: 4 pages, 3 figure

Russian and American Poetry: Towards New Language Abilities

The book by Vladimir Feshchenko, a Russian researcher of the language of poetry and a publisher of avant-garde literature, is devoted to Russian and American poetry of the language experiment in the 20th and early 21st century. Using examples from Andrei Bely, Russian futurists, Alexander Vvedensky, Ezra Pound, Gertrude Stein, E.E. Cummings to the American poets of “language writing” and modern Russian-speaking young poets, the similarity of the philosophical and linguistic foundations of the language experiment, the convergence and differences of literatures, the personal interaction of authors from both countries are considered in the book. The analysis of a number of American and Russian poems from the point of view of the language of poetry is given. V. Feshchenko's book is of interest to researchers of Russian and American poetry, the avant-garde, the language of poetry, and the interaction of literatures

Annealing by simulating the coherent Ising machine

The coherent Ising machine (CIM) enables efficient sampling of low-lying energy states of the Ising Hamiltonian with all-to-all connectivity by encoding the spins in the amplitudes of pulsed modes in an optical parametric oscillator (OPO). The interaction between the pulses is realized by means of measurement-based optoelectronic feedforward which enhances the gain for lower-energy spin configurations. We present an efficient method of simulating the CIM on a classical computer that outperforms the CIM itself as well as the noisy mean-field annealer in terms of both the quality of the samples and the computational speed. It is furthermore advantageous with respect to the CIM in that it can handle Ising Hamiltonians with arbitrary real-valued node coupling strengths. These results illuminate the nature of the faster performance exhibited by the CIM and may give rise to a new class of quantum-inspired algorithms of classical annealing that can successfully compete with existing methods