96,045 research outputs found
Calibration of centre-of-mass energies at LEP 2 for a precise measurement of the W boson mass
The determination of the centre-of-mass energies for all LEP 2 running is
presented. Accurate knowledge of these energies is of primary importance to set
the absolute energy scale for the measurement of the W boson mass. The beam
energy between 80 and 104 GeV is derived from continuous measurements of the
magnetic bending field by 16 NMR probes situated in a number of the LEP
dipoles. The relationship between the fields measured by the probes and the
beam energy is defined in the NMR model, which is calibrated against precise
measurements of the average beam energy between 41 and 61 GeV made using the
resonant depolarisation technique. The validity of the NMR model is verified by
three independent methods: the flux-loop, which is sensitive to the bending
field of all the dipoles of LEP; the spectrometer, which determines the energy
through measurements of the deflection of the beam in a magnet of known
integrated field; and an analysis of the variation of the synchrotron tune with
the total RF voltage. To obtain the centre-of-mass energies, corrections are
then applied to account for sources of bending field external to the dipoles,
and variations in the local beam energy at each interaction point. The relative
error on the centre-of-mass energy determination for the majority of LEP 2
running is 1.2 x 10^{-4}, which is sufficiently precise so as not to introduce
a dominant uncertainty on the W mass measurement.Comment: 79 pages, 45 figures, submitted to EPJ
Scalable and Sustainable Deep Learning via Randomized Hashing
Current deep learning architectures are growing larger in order to learn from
complex datasets. These architectures require giant matrix multiplication
operations to train millions of parameters. Conversely, there is another
growing trend to bring deep learning to low-power, embedded devices. The matrix
operations, associated with both training and testing of deep networks, are
very expensive from a computational and energy standpoint. We present a novel
hashing based technique to drastically reduce the amount of computation needed
to train and test deep networks. Our approach combines recent ideas from
adaptive dropouts and randomized hashing for maximum inner product search to
select the nodes with the highest activation efficiently. Our new algorithm for
deep learning reduces the overall computational cost of forward and
back-propagation by operating on significantly fewer (sparse) nodes. As a
consequence, our algorithm uses only 5% of the total multiplications, while
keeping on average within 1% of the accuracy of the original model. A unique
property of the proposed hashing based back-propagation is that the updates are
always sparse. Due to the sparse gradient updates, our algorithm is ideally
suited for asynchronous and parallel training leading to near linear speedup
with increasing number of cores. We demonstrate the scalability and
sustainability (energy efficiency) of our proposed algorithm via rigorous
experimental evaluations on several real datasets
Radioactive Needlework, Reconstruction of needle-positions in radiation treatment
Nucletron presented a medical problem to the SWI 2006: how to find needles used for cancer treatment in a prostate? More concretely: how to find the positions of these needles from distorted images from an ultrasound probe? Section 1 explains the background of this problem. In Section 2 we deal with physical explanations for the distortions. In Section 3 we give a brief overview of medical imaging and explain which techniques we used to clean up the images
The International Linear Collider
In this article, we describe the key features of the recently completed
technical design for the International Linear Collider (ILC), a 200-500 GeV
linear electron-positron collider (expandable to 1 TeV) that is based on 1.3
GHz superconducting radio-frequency (SCRF) technology. The machine parameters
and detector characteristics have been chosen to complement the Large Hadron
Collider physics, including the discovery of the Higgs boson, and to further
exploit this new particle physics energy frontier with a precision instrument.
The linear collider design is the result of nearly twenty years of R&D,
resulting in a mature conceptual design for the ILC project that reflects an
international consensus. We summarize the physics goals and capability of the
ILC, the enabling R&D and resulting accelerator design, as well as the concepts
for two complementary detectors. The ILC is technically ready to be proposed
and built as a next generation lepton collider, perhaps to be built in stages
beginning as a Higgs factory.Comment: 41 page
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