134 research outputs found
Decoherence of quantum states and its suppression in ensemble large-scale solid state NMR quantum computers
It is discussed the decoherence problems in ensemble large-scale solid state
NMR quantum computer based on the array of P donor atoms having nuclear spin I
= 1/2. It is considered here, as main mechanisms of decoherence for low
temperature (< 0.1 K), the adiabatic processes of random modulation of qubit
resonance frequency determined by secular part of nuclear spin interaction with
electron spin of the basic atoms, with impurity paramagnetic atoms and also
with nuclear spins of impurity diamagnetic atoms. It was made estimations of
allowed concentrations of magnetic impurities and of spin temperature whereby
the required decoherence suppression is obtained. It is discussed the random
phase error suppression in the ensemble quantum register basic states.Comment: LaTeX 7 pages. Submitted to Proceedings of SPIE. International
Symposium Quantum Informatics (QI-2002), October 2002, Zvenigorod, Russi
The controlled indirect coupling between spatially-separated qubits in antiferromagnet-based NMR quantum registers
It is considered the indirect inter-qubit coupling in 1D chain of atoms with
nuclear spins 1/2, which plays role of qubits in the quantum register. This
chain of the atoms is placed by regular way in easy-axis 3D antiferromagnetic
thin plate substrate, which is cleaned from the other nuclear spin containing
isotopes. It is shown that the range of indirect inter-spin coupling may run to
a great number of lattice constants both near critical point of quantum phase
transition in antiferromagnet of spin-flop type (control parameter is external
magnetic field) and/or near homogeneous antiferromagnetic resonance (control
parameter is microwave frequency).Comment: Latex 5 pages, 1 figure. Presented at International Symposium
"Quantum Informatics 2004" Moscow, October 5-8, 2004. Will be published in
Proc. SPI
Fuzzy neural networks' application for substation integral state assessment
This paper addresses the problems connected with fuzzy neural networks' application in equipment technical state assessment problems at electrical substations. This paper discusses the main principles of fuzzy neural network formation and its construction algorithm. Also, the case study for the determination of fuzzy neural network synaptic weights for the unit "disconnector" on the basis of technical diagnostic statistical data and tests is presented. Β© 2014 WIT Press.International Journal of Safety and Security Engineering;International Journal of Sustainable Development and Planning;WIT Transactions on Ecology and the Environmen
ΠΡΠΎΠ±Π»Π΅ΠΌΠ° ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠΎΠ²ΡΡ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² Π² ΡΡΠ΄Π΅Π±Π½ΠΎ-Π±Π°Π»Π»ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ
The Russian school of forensic firearms investigation traditionally recognizes common and individual features of traces on bullets and cartridge cases. The first are characteristics inherent in all weapons of the same model and describing their details in general: shape, size, location, relative position. The second type are individual characteristics, which are unique and present only in one firearm. The individual features are used for forensic identification, while the common can be used only for the identification of a firearmβs type and model. Β The Western (West Europe and the USA) methodology of forensic ballistic identification recognizes the third type of traits β subclass characteristics. These marks are the result of manufacturing processes and can be present in a group of sequentially produced parts. Conventionally they can be placed between class and individual characteristics. One of the problems in contemporary firearms identification is the wrong recognition of subclass marks as individual marks and, as a result, giving false-positive conclusions of identification. Β The article discusses the problem of subclass features, gives examples, presents a review of the literature. The influence of various technological processes on the possibility of showing up of these marks is described. Β Π ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ ΡΠΊΠΎΠ»Π΅ ΡΡΠ΄Π΅Π±Π½ΠΎ-Π±Π°Π»Π»ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ Π² ΡΠ»Π΅Π΄Π°Ρ
ΠΎΡΡΠΆΠΈΡ Π½Π° ΠΏΡΠ»ΡΡ
ΠΈ Π³ΠΈΠ»ΡΠ·Π°Ρ
ΠΏΡΠΈΠ½ΡΡΠΎ Π²ΡΠ΄Π΅Π»ΡΡΡ ΠΎΠ±ΡΠΈΠ΅ ΠΈ ΡΠ°ΡΡΠ½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ. ΠΠ΅ΡΠ²Π°Ρ Π³ΡΡΠΏΠΏΠ° β ΡΡΠΎ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ, ΠΏΡΠΈΡΡΡΠΈΠ΅ Π²ΡΠ΅ΠΌ ΡΠΊΠ·Π΅ΠΌΠΏΠ»ΡΡΠ°ΠΌ ΠΎΡΡΠΆΠΈΡ ΠΎΠ΄Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠ΅ ΠΈΡ
Π΄Π΅ΡΠ°Π»ΠΈ Π² ΡΠ΅Π»ΠΎΠΌ: ΡΠΎΡΠΌΠ°, ΡΠ°Π·ΠΌΠ΅ΡΡ, ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅, Π²Π·Π°ΠΈΠΌΠΎΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅. ΠΡΠΎΡΠ°Ρ Π³ΡΡΠΏΠΏΠ° β ΡΡΠΎ ΡΠ°ΡΡΠ½ΡΠ΅ (ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΡΠ½ΡΠ΅) ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ, ΠΊΠΎΒΡΠΎΡΡΠ΅ ΡΠ½ΠΈΠΊΠ°Π»ΡΠ½Ρ ΠΈ ΠΏΡΠΎΡΠ²Π»ΡΡΡΡΡ ΡΠΎΠ»ΡΠΊΠΎ Π² ΠΎΠ΄Π½ΠΎΠΌ ΡΠΊΠ·Π΅ΠΌΠΏΠ»ΡΡΠ΅ ΠΎΡΡΠΆΠΈΡ. Π§Π°ΡΡΠ½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΒΡΡΡΡ Π΄Π»Ρ ΠΊΡΠΈΠΌΠΈΠ½Π°Π»ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ, Π² ΡΠΎ Π²ΡΠ΅ΠΌΡ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠΈΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΌΠΎΠ³ΡΡ ΠΏΡΠΈΠΌΠ΅Π½ΡΡΡΡΡ ΡΠΎΠ»ΡΠΊΠΎ Π΄Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠΈΠΏΠ° ΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΎΠ³Π½Π΅ΡΡΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΡΡΠΆΠΈΡ. Β Π Π·Π°ΠΏΠ°Π΄Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ (ΠΠ²ΡΠΎΠΏΠ° ΠΈ Π‘Π¨Π) ΡΡΠ΄Π΅Π±Π½ΠΎ-Π±Π°Π»Π»ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ Π²ΡΠ΄Π΅Π»ΡΠ΅ΡΡΡ Π΅ΡΠ΅ ΠΈ ΡΡΠ΅ΡΠΈΠΉ ΡΠΈΠΏ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² β ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠΎΠ²ΡΠ΅. ΠΡΠΈ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΠ²Π»ΡΡΡΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠΌ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΠΈ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ Π² ΠΈΡ
ΡΠ»Π΅Π΄Π°Ρ
Π² Π³ΡΡΠΏΠΏΠ΅ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΈΠ·Π³ΠΎΡΠΎΠ²Π»Π΅Π½Π½ΡΡ
Π΄Π΅ΒΡΠ°Π»Π΅ΠΉ. Π£ΡΠ»ΠΎΠ²Π½ΠΎ ΠΈΡ
ΠΌΠΎΠΆΠ½ΠΎ ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠΈΡΡ ΠΌΠ΅ΠΆΠ΄Ρ ΠΎΠ±ΡΠΈΠΌΠΈ ΠΈ ΡΠ°ΡΡΠ½ΡΠΌΠΈ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌΠΈ. ΠΠ΄Π½ΠΎΠΉ ΠΈΠ· ΠΏΡΠΎΠ±Π»Π΅ΠΌ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΎΠ³Π½Π΅ΡΡΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΡΡΠΆΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ Π»ΠΎΠΆΠ½ΠΎΠ΅ Π²ΠΎΡΠΏΡΠΈΡΡΠΈΠ΅ ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠΎΠ²ΡΡ
ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² ΠΊΠ°ΠΊ ΡΠ°ΡΡΠ½ΡΡ
ΠΈ, ΠΊΠ°ΠΊ ΡΠ΅Π·ΡΠ»ΡΡΠ°Ρ, ΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΎΡΠΈΠ±ΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ Π²ΡΠ²ΠΎΠ΄Π° ΠΎ ΡΠΎΠΆΠ΄Π΅ΡΡΠ²Π΅. Β Π ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Π° ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ° ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠΎΠ²ΡΡ
ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ², ΠΏΡΠΈΠ²Π΅Π΄Π΅Π½Ρ ΠΏΡΠΈΠΌΠ΅ΡΡ ΠΈ ΠΎΠ±Π·ΠΎΡ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΡ. ΠΠΏΠΈΡΠ°Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π½Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΏΡΠΎΡΠ²Π»Π΅Π½ΠΈΡ ΡΡΠΎΠ³ΠΎ ΡΠΈΠΏΠ° ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ².
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