Quantum estimation via sequential measurements

The problem of estimating a parameter of a quantum system through a series of measurements performed sequentially on a quantum probe is analyzed in the general setting where the underlying statistics is explicitly non-i.i.d. We present a generalization of the central limit theorem in the present context, which under fairly general assumptions shows that as the number $N$ of measurement data increases the probability distribution of functionals of the data (e.g., the average of the data) through which the target parameter is estimated becomes asymptotically normal and independent of the initial state of the probe. At variance with the previous studies [M. Gu\c{t}\u{a}, Phys. Rev. A 83, 062324 (2011); M. van Horssen and M. Gu\c{t}\u{a}, J. Math. Phys. 56, 022109 (2015)] we take a diagrammatic approach, which allows one to compute not only the leading orders in $N$ of the moments of the average of the data but also those of the correlations among subsequent measurement outcomes. In particular our analysis points out that the latter, which are not available in usual i.i.d. data, can be exploited in order to improve the accuracy of the parameter estimation. An explicit application of our scheme is discussed by studying how the temperature of a thermal reservoir can be estimated via sequential measurements on a quantum probe in contact with the reservoir.Comment: 20 pages, 10 figure

Automatic Computation of Cross Sections in HEP

For the study of reactions in High Energy Physics (HEP) automatic computation systems have been developed and are widely used nowadays. GRACE is one of such systems and it has achieved much success in analyzing experimental data. Since we deal with the cross section whose value can be given by calculating hundreds of Feynman diagrams, we manage the large scale calculation, so that effective symbolic manipulation, the treat of singularity in the numerical integration are required. The talk will describe the software design of GRACE system and computational techniques in the GRACE.Comment: 6 pages, Latex, ICCP

MOTION ANALYSIS OF TRUNK WITH LUMBAR CORSET DURING WALKING IN YOUNG WOMEN

INTRODUCTION: In the study of walking, there are many studies that have analyzed the joint angle, the joint torques and muscle activity in lower limb. However, walking is a movement from head to foot and it is important to analyze trunk movement. Lately, sports activity of handicapped people and older adults have become popular. When handicapped people and older adults exercise, they often used an athletic supporter and a lumbar corset to assist movement of the hip joint. The main effects of the corset are that it limits trunk excursion, aiding bodily movement. The aim of present study was to investigate whether the lumbar corset influences trunk motion in the sagittal plane during walking

Microwave neural processing and broadcasting with spintronic nano-oscillators

Can we build small neuromorphic chips capable of training deep networks with billions of parameters? This challenge requires hardware neurons and synapses with nanometric dimensions, which can be individually tuned, and densely connected. While nanosynaptic devices have been pursued actively in recent years, much less has been done on nanoscale artificial neurons. In this paper, we show that spintronic nano-oscillators are promising to implement analog hardware neurons that can be densely interconnected through electromagnetic signals. We show how spintronic oscillators maps the requirements of artificial neurons. We then show experimentally how an ensemble of four coupled oscillators can learn to classify all twelve American vowels, realizing the most complicated tasks performed by nanoscale neurons