113,973 research outputs found
Algorithmic Cooling of Spins: A Practicable Method for Increasing Polarization
An efficient technique to generate ensembles of spins that are highly
polarized by external magnetic fields is the Holy Grail in Nuclear Magnetic
Resonance (NMR) spectroscopy. Since spin-half nuclei have steady-state
polarization biases that increase inversely with temperature, spins exhibiting
high polarization biases are considered cool, even when their environment is
warm. Existing spin-cooling techniques are highly limited in their efficiency
and usefulness. Algorithmic cooling is a promising new spin-cooling approach
that employs data compression methods in open systems. It reduces the entropy
of spins on long molecules to a point far beyond Shannon's bound on reversible
entropy manipulations (an information-theoretic version of the 2nd Law of
Thermodynamics), thus increasing their polarization. Here we present an
efficient and experimentally feasible algorithmic cooling technique that cools
spins to very low temperatures even on short molecules. This practicable
algorithmic cooling could lead to breakthroughs in high-sensitivity NMR
spectroscopy in the near future, and to the development of scalable NMR quantum
computers in the far future. Moreover, while the cooling algorithm itself is
classical, it uses quantum gates in its implementation, thus representing the
first short-term application of quantum computing devices.Comment: 24 pages (with annexes), 3 figures (PS). This version contains no
major content changes: fixed bibliography & figures, modified
acknowledgement
Performance of a cryogenic system prototype for the XENON1T Detector
We have developed an efficient cryogenic system with heat exchange and
associated gas purification system, as a prototype for the XENON1T experiment.
The XENON1T detector will use about 3 ton of liquid xenon (LXe) at a
temperature of 175K as target and detection medium for a dark matter search. In
this paper we report results on the cryogenic system performance focusing on
the dynamics of the gas circulation-purification through a heated getter, at
flow rates above 50 Standard Liter per Minute (SLPM). A maximum flow of 114
SLPM has been achieved, and using two heat exchangers in parallel, a heat
exchange efficiency better than 96% has been measured
On Idle Energy Consumption Minimization in Production: Industrial Example and Mathematical Model
This paper, inspired by a real production process of steel hardening,
investigates a scheduling problem to minimize the idle energy consumption of
machines. The energy minimization is achieved by switching a machine to some
power-saving mode when it is idle. For the steel hardening process, the mode of
the machine (i.e., furnace) can be associated with its inner temperature.
Contrary to the recent methods, which consider only a small number of machine
modes, the temperature in the furnace can be changed continuously, and so an
infinite number of the power-saving modes must be considered to achieve the
highest possible savings. To model the machine modes efficiently, we use the
concept of the energy function, which was originally introduced in the domain
of embedded systems but has yet to take roots in the domain of production
research. The energy function is illustrated with several application examples
from the literature. Afterward, it is integrated into a mathematical model of a
scheduling problem with parallel identical machines and jobs characterized by
release times, deadlines, and processing times. Numerical experiments show that
the proposed model outperforms a reference model adapted from the literature.Comment: Accepted to 9th International Conference on Operations Research and
Enterprise Systems (ICORES 2020
- …