185 research outputs found
Π€ΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
The analytical value of the complex system of statistical indicators characterizing the creation of value in the primary real estate market is determined by the sensitivity of the entire socio-economic sphere to the object of study, since it is the population, that is, the end user of this element of national accumulation, feels it as a factor of living standards, welfare, material potential and even as the possibility of obtaining passive income in the form of property rent.The secondary market of residential real estate, where a huge share of cash savings of the population turns out, is partly inferior in its importance to the primary market. This applies to the fact that the primary market is the relationship of the subjects about not only the movement, but also the creation of value. Thus, we are talking about the circulation of tangible assets, which are an integral part of the new, newly created gross domestic product, namely that part of it that is not consumed as part of final consumption, but represents gross capital formation β the accumulation of fixed capital.Purpose. Presentation of statistical methodology content, relating to the language of any statistical study β indicators, in this case the systematization and ordering of a comprehensive system of indicators of statistics of the creation of objects in the primary real estate market.Materials and methods. Since the article is of a methodological nature, it uses the methods of general scientific knowledge, synthesis, generalization of qualitative information, based objectively on Β dialectical unity with natural and special sciences, primarily engineering and construction, relating to the object of statistical research, and mathematical, concerning the methodological aspects of obtaining quantitative estimates of the statistical indicators.In the statistics of living standards of the population, considerable attention is paid to the level of consumer spending of households. These are, directly, monetary expenses per capita, specific indicators of retail trade turnover and payment for services. However, only the statistics of the primary market and the characteristics of the creation of new facilities can show the participation of the population in the financing of the growth of national wealth, that part of it, which is determined by the international methodology, as the accumulated property created by the work of current and previous generations.It should be noted that the statistical analysis of the primary real estate market and the complex processes of creating objects that turn on it, is associated with a certain Russian paradox: a large-scale information attack, which is subjected to the domestic society, says about the reduction in recent years the standard of living of the population on various parameters, including the range and quantity of food consumption; at the same time, the volume of the area entered and realized in the primary real estate market, exactly, as well as the prices for it, grow uncontrollably that indicates inexhaustible solvent demand of the population for the acquired objects of long-term use.Results. In the research paper the information sources are ordered, the blocks of statistical indicators are consistently built, allowing to obtain both primary and generalized characteristics of the commissioning of primary objects related to both housing directly and to communication facilities that provide residential functionality of the results of construction and the entire residential infrastructure.Conclusion. The article deals with the analytical potential of indicators along with the prospects of their further application and the possibility of further improvement of statistical methodology and improving the quality of research of such a complex object as the primary real estate market.ΠΠ½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠ΅Π½Π½ΠΎΡΡΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΡ
ΡΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡΡ Π²ΡΠ΅ΠΉ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ΅ΡΡ ΠΈΠΌΠ΅Π½Π½ΠΎ ΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΈΠΌΠ΅Π½Π½ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΠ΅, ΡΠΎ Π΅ΡΡΡ ΠΊΠΎΠ½Π΅ΡΠ½ΡΠΉ ΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΠ΅Π»Ρ ΡΡΠΎΠ³ΠΎ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠ° Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½ΠΈΡ, ΠΎΡΡΡΠ°Π΅Ρ Π΅Π³ΠΎ Π½Π° ΡΠ΅Π±Π΅ ΠΊΠ°ΠΊ ΡΠ°ΠΊΡΠΎΡ ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ, Π±Π»Π°Π³ΠΎΡΠΎΡΡΠΎΡΠ½ΠΈΡ, ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»Π° ΠΈ, Π΄Π°ΠΆΠ΅, ΠΊΠ°ΠΊ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΡΠΈΠ²Π½ΠΎΠ³ΠΎ Π΄ΠΎΡ
ΠΎΠ΄Π° Π² Π²ΠΈΠ΄Π΅ ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠ΅Π½ΡΡ.ΠΡΠΎΡΠΈΡΠ½ΡΠΉ ΡΡΠ½ΠΎΠΊ ΠΆΠΈΠ»ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, Π³Π΄Π΅ ΠΎΠ±ΠΎΡΠ°ΡΠΈΠ²Π°Π΅ΡΡΡ ΠΎΠ³ΡΠΎΠΌΠ½Π°Ρ Π΄ΠΎΠ»Ρ Π΄Π΅Π½Π΅ΠΆΠ½ΡΡ
Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½ΠΈΠΉ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΠΎΡΡΠ°ΡΡΠΈ ΡΡΡΡΠΏΠ°Π΅Ρ ΡΠ²ΠΎΠ΅ΠΉ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌΡ ΡΡΠ½ΠΊΡ. ΠΡΠΎ ΠΊΠ°ΡΠ°Π΅ΡΡΡ ΡΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠΎΡΡΠ΅Π»ΡΡΡΠ²Π°, ΡΡΠΎ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΠΉ ΡΡΠ½ΠΎΠΊ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠΎΠ±ΠΎΠΉ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΏΠΎ ΠΏΠΎΠ²ΠΎΠ΄Ρ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ, Π½ΠΎ ΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ ΡΠ΅ΡΡ ΠΈΠ΄ΡΡ ΠΎΠ± ΠΎΠ±ΡΠ°ΡΠ΅Π½ΠΈΠΈ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠ²Π»ΡΡΡΡΡ ΡΠΎΡΡΠ°Π²Π½ΠΎΠΉ ΡΠ°ΡΡΡΡ Π½ΠΎΠ²ΠΎΠ³ΠΎ, Π²Π½ΠΎΠ²Ρ ΡΠΎΠ·Π΄Π°Π½Π½ΠΎΠ³ΠΎ Π²Π°Π»ΠΎΠ²ΠΎΠ³ΠΎ Π²Π½ΡΡΡΠ΅Π½Π½Π΅Π³ΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΠ°, Π° ΠΈΠΌΠ΅Π½Π½ΠΎ ΡΠΎΠΉ Π΅Π³ΠΎ ΡΠ°ΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ Π½Π΅ ΠΏΠΎΡΡΠ΅Π±Π»ΡΠ΅ΡΡΡ Π² ΡΠΎΡΡΠ°Π²Π΅ ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ, Π° ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠΎΠ±ΠΎΠΉ Π²Π°Π»ΠΎΠ²ΠΎΠ΅ ΠΊΠ°ΠΏΠΈΡΠ°Π»ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ β Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½ΠΈΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΊΠ°ΠΏΠΈΡΠ°Π»Π°.Π¦Π΅Π»Ρ: ΠΠ°Π»ΡΠ½Π΅ΠΉΡΠ΅Π΅ ΡΠ°ΡΠΊΡΡΡΠΈΠ΅ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠ°ΡΡΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΊΠ°ΡΠ°ΡΡΠ΅ΠΉΡΡ ΡΠ·ΡΠΊΠ° Π»ΡΠ±ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, Π² Π΄Π°Π½Π½ΠΎΠΌ ΡΠ»ΡΡΠ°Π΅ β ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ ΠΈ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½ΠΈΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠΎΡΠΊΠΎΠ»ΡΠΊΡ ΡΡΠ°ΡΡΡ Π½ΠΎΡΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ, Π² Π½Π΅ΠΉ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΎΠ±ΡΠ΅Π½Π°ΡΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ, ΡΠΈΠ½ΡΠ΅Π·Π°, ΠΎΠ±ΠΎΠ±ΡΠ΅Π½ΠΈΡ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ, Π±Π°Π·ΠΈΡΡΡΡΠΈΠ΅ΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ Π½Π° Π΄ΠΈΠ°Π»Π΅ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΌ Π΅Π΄ΠΈΠ½ΡΡΠ²Π΅ Ρ Π΅ΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ ΠΈ ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΠΌΠΈ Π½Π°ΡΠΊΠ°ΠΌΠΈ, Π² ΠΏΠ΅ΡΠ²ΡΡ ΠΎΡΠ΅ΡΠ΅Π΄Ρ β ΠΈΠ½ΠΆΠ΅Π½Π΅ΡΠ½ΠΎ-ΡΡΡΠΎΠΈΡΠ΅Π»ΡΠ½ΡΠΌΠΈ, ΠΊΠ°ΡΠ°ΡΡΠΈΠΌΠΈΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ, ΠΊΠ°ΡΠ°ΡΡΠΈΠΌΠΈΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΡΠΏΠ΅ΠΊΡΠΎΠ² ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΎΡΠ΅Π½ΠΎΠΊ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΡΡ
ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ.Π ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ΅ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΡΠ΄Π΅Π»ΡΠ΅ΡΡΡ ΡΡΠΎΠ²Π½Ρ ΠΏΠΎΡΡΠ΅Π±ΠΈΡΠ΅Π»ΡΡΠΊΠΈΡ
ΡΠ°ΡΡ
ΠΎΠ΄ΠΎΠ² Π΄ΠΎΠΌΠ°ΡΠ½ΠΈΡ
Ρ
ΠΎΠ·ΡΠΉΡΡΠ². ΠΡΠΎ ΠΈ, Π½Π΅ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²Π΅Π½Π½ΠΎ, Π΄Π΅Π½Π΅ΠΆΠ½ΡΠ΅ ΡΠ°ΡΡ
ΠΎΠ΄Ρ Π½Π° Π΄ΡΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΡΠ΄Π΅Π»ΡΠ½ΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΡΠΎΠ·Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΠΎΠ²Π°ΡΠΎΠΎΠ±ΠΎΡΠΎΡΠ° ΠΈ ΠΎΠΏΠ»Π°ΡΡ ΡΡΠ»ΡΠ³. ΠΠ΄Π½Π°ΠΊΠΎ, ΡΠΎΠ»ΡΠΊΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠΎΠ·Π΄Π°Π½ΠΈΡ Π½ΠΎΠ²ΡΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΌΠΎΠΆΠ΅Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΡ ΡΡΠ°ΡΡΠΈΠ΅ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π² ΡΠΈΠ½Π°Π½ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΈΡΠΎΡΡΠ° Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΠΎΠ³Π°ΡΡΡΠ²Π°, ΡΠΎΠΉ Π΅Π³ΠΎ ΡΠ°ΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ ΠΏΠΎ ΠΌΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΊΠ°ΠΊ Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½Π½ΠΎΠ΅ ΠΈΠΌΡΡΠ΅ΡΡΠ²ΠΎ, ΡΠΎΠ·Π΄Π°Π½Π½ΠΎΠ΅ ΡΡΡΠ΄ΠΎΠΌ Π½ΡΠ½Π΅ΡΠ½Π΅Π³ΠΎ ΠΈ ΠΏΡΠ΅Π΄ΡΠ΄ΡΡΠΈΡ
ΠΏΠΎΠΊΠΎΠ»Π΅Π½ΠΈΠΉ.ΠΡΠΌΠ΅ΡΠΈΠΌ, ΡΡΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΈ ΡΠ»ΠΎΠΆΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ², ΠΊΠΎΡΠΎΡΡΠ΅ ΠΎΠ±ΡΠ°ΡΠ°ΡΡΡΡ Π½Π° Π½ΡΠΌ, ΡΠΎΠΏΡΡΠΆΡΠ½ Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ½Π½ΡΠΌ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΠΌ ΠΏΠ°ΡΠ°Π΄ΠΎΠΊΡΠΎΠΌ: ΠΌΠ°ΡΡΡΠ°Π±Π½Π°Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½Π°Ρ Π°ΡΠ°ΠΊΠ°, ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΠΎΠ΄Π²Π΅ΡΠ³Π°Π΅ΡΡΡ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ ΡΠΎΡΠΈΡΠΌ, Π³Π»Π°ΡΠΈΡ ΠΎ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠΈ Π·Π° ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΠ΅ Π³ΠΎΠ΄Ρ ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΏΠΎ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°ΠΌ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ ΠΏΠΎ Π°ΡΡΠΎΡΡΠΈΠΌΠ΅Π½ΡΡ ΠΈ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Ρ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ² ΠΏΠΈΡΠ°Π½ΠΈΡ; ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ, ΠΎΠ±ΡΠ΅ΠΌ Π²Π²ΠΎΠ΄ΠΈΠΌΠΎΠΉ ΠΈ ΡΠ΅Π°Π»ΠΈΠ·ΡΠ΅ΠΌΠΎΠΉ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΏΠ»ΠΎΡΠ°Π΄ΠΈ, ΡΠΎΠ²Π½ΠΎ, ΠΊΠ°ΠΊ ΠΈ ΡΠ΅Π½Ρ Π½Π° Π½Π΅Ρ, ΡΠ°ΡΡΡΡ Π½Π΅ΡΠ΄Π΅ΡΠΆΠΈΠΌΠΎ, ΡΡΠΎ ΡΠΊΠ°Π·ΡΠ²Π°Π΅Ρ Π½Π° Π½Π΅ΠΈΡΡΡΠΊΠ°Π΅ΠΌΡΠΉ ΠΏΠ»Π°ΡΡΠΆΠ΅ΡΠΏΠΎΡΠΎΠ±Π½ΡΠΉ ΡΠΏΡΠΎΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π½Π° ΠΏΡΠΈΠΎΠ±ΡΠ΅ΡΠ°Π΅ΠΌΡΠ΅ ΠΎΠ±ΡΠ΅ΠΊΡΡ Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π Π½Π°ΡΡΠ½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ, ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎ Π²ΡΡΡΡΠΎΠ΅Π½Ρ Π±Π»ΠΎΠΊΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΠ΅ ΠΏΠΎΠ»ΡΡΠΈΡΡ, ΠΊΠ°ΠΊ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ, ΡΠ°ΠΊ ΠΈ ΠΎΠ±ΠΎΠ±ΡΡΠ½Π½ΡΡ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΡ Π²Π²ΠΎΠ΄Π° Π² Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ², ΠΎΡΠ½ΠΎΡΠΈΠΌΡΡ
, ΠΊΠ°ΠΊ ΠΊ ΠΆΠΈΠ»ΡΡ Π½Π΅ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²Π΅Π½Π½ΠΎ, ΡΠ°ΠΊ ΠΈ ΠΊ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΠΌ ΡΠΎΠΎΡΡΠΆΠ΅Π½ΠΈΡΠΌ, ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°ΡΡΠΈΠΌ ΠΆΠΈΠ»ΠΎΠΉ ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π» ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΡΡΡΠΎΠΈΡΠ΅Π»ΡΡΡΠ²Π° ΠΈ Π²ΡΠ΅ΠΉ ΠΆΠΈΠ»ΠΎΠΉ ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΡ.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. Π ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π» ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π½Π°ΡΡΠ΄Ρ Ρ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π°ΠΌΠΈ ΠΈΡ
Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅Π³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡΡ Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅Π³ΠΎ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ ΡΠ»ΡΡΡΠ΅Π½ΠΈΡ ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΡΠΎΠ»Ρ ΡΠ»ΠΎΠΆΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΊΠ°ΠΊ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΠΉ ΡΡΠ½ΠΎΠΊ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ Π°ΠΊΡΠΈΠ²ΠΎΠ²
The article is devoted to consideration and evaluation of machinery, equipment and special equipment, methodological aspects of the use of standards for assessment of buildings and structures in current prices, the valuation of residential, specialized houses, office premises, assessment and reassessment of existing and inactive military assets, the application of statistical methods to obtain the relevant cost estimates.The objective of the scientific article is to consider possible application of statistical tools in the valuation of the assets, composing the core group of elements of national wealth β the fixed assets. Firstly, capital tangible assets constitute the basis of material base of a new value creation, products and non-financial services. The gain, accumulated of tangible assets of a capital nature is a part of the gross domestic product, and from its volume and specific weight in the composition of GDP we can judge the scope of reproductive processes in the country.Based on the methodological materials of the state statistics bodies of the Russian Federation, regulations of the theory of statistics, which describe the methods of statistical analysis such as the index, average values, regression, the methodical approach is structured in the application of statistical tools to obtain value estimates of property, plant and equipment with significant accumulated depreciation. Until now, the use of statistical methodology in the practice of economic assessment of assets is only fragmentary. This applies to both Federal Legislation (Federal law β 135 Β«On valuation activities in the Russian FederationΒ» dated 16.07.1998 in edition 05.07.2016) and the methodological documents and regulations of the estimated activities, in particular, the valuation activitiesβ standards. A particular problem is the use of a digital database of Rosstat (Federal State Statistics Service), as to the specific fixed assets the comparison should be carried out precisely in the boundary of the typological group to which the object is identified.The rationale for the comprehensive application of statistical methods in the implementation of cost and comparative approaches in the assessment of economic assets, practical component, are a primary result of scientific research. It is not enough to use methodological developments in the assessment activities in modern conditions of market development and scientific and technical level for the large-scale evaluation of all available material resources of the economy and their total potential. The application of mathematical-statistical apparatus, therefore, is an objective necessity for obtaining general indicators of the size of the national wealth.In conclusion, we can mention about the methodical approaches, the building of model algorithms application of statistical methods in solving scientific and practical problems, depending on the identification belonging of the valued objects. It is premature to talk about the formalization of the application of statistical methods, the results of which would be transformed into a Ρertain reporting. It requires the solution of a question on the fixed assetsβ census at least at the level of regions, subjects of the Russian Federation.ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΠ°Ρ ΡΡΠ°ΡΡΡ ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° ΡΡΠ΅ΡΡ ΠΈ ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΌΠ°ΡΠΈΠ½, ΠΎΠ±ΠΎΡΡΠ΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΡΠ΅Ρ
Π½ΠΈΠΊΠΈ, ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ Π°ΡΠΏΠ΅ΠΊΡΠ°ΠΌ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ, ΠΊΠ°ΠΊ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΉ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠΈ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π·Π΄Π°Π½ΠΈΠΉ ΠΈ ΡΠΎΠΎΡΡΠΆΠ΅Π½ΠΈΠΉ Π² ΡΠ΅ΠΊΡΡΠΈΡ
ΡΠ΅Π½Π°Ρ
, ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΆΠΈΠ»ΡΡ
, ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π΄ΠΎΠΌΠΎΠ², ΡΠ»ΡΠΆΠ΅Π±Π½ΡΡ
ΠΆΠΈΠ»ΡΡ
ΠΏΠΎΠΌΠ΅ΡΠ΅Π½ΠΈΠΉ, ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΈ ΠΏΠ΅ΡΠ΅ΠΎΡΠ΅Π½ΠΊΠ΅ Π΄Π΅ΠΉΡΡΠ²ΡΡΡΠΈΡ
ΠΈ Π·Π°ΠΊΠΎΠ½ΡΠ΅ΡΠ²ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π²ΠΎΠ΅Π½Π½ΡΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ², ΡΠ°ΠΊ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΡ
ΡΡΠΎΠΈΠΌΠΎΡΡΠ½ΡΡ
ΠΎΡΠ΅Π½ΠΎΠΊ. Π¦Π΅Π»Ρ Π½Π°ΡΡΠ½ΠΎΠΉ ΡΡΠ°ΡΡΠΈ Π²ΡΠ·Π°Π½Π° Ρ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½ΠΈΠ΅ΠΌ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡ Π² ΡΡΠΎΠΈΠΌΠΎΡΡΠ½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠ΅ Π°ΠΊΡΠΈΠ²ΠΎΠ², ΡΠ»Π°Π³Π°ΡΡΠΈΡ
ΠΊΠ»ΡΡΠ΅Π²ΡΡ Π³ΡΡΠΏΠΏΡ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΠΎΠ³Π°ΡΡΡΠ²Π° β ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ². ΠΠΌΠ΅Π½Π½ΠΎ ΠΊΠ°ΠΏΠΈΡΠ°Π»ΡΠ½ΡΠ΅ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΠ΅ Π°ΠΊΡΠΈΠ²Ρ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΡΡ ΡΠΎΠ±ΠΎΠΉ ΠΎΡΠ½ΠΎΠ²Ρ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π°Π·Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ Π½ΠΎΠ²ΠΎΠΉ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ β Π² ΠΏΠ΅ΡΠ²ΡΡ ΠΎΡΠ΅ΡΠ΅Π΄Ρ, ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ² ΠΈ Π½Π΅ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΡΡ
ΡΡΠ»ΡΠ³. ΠΡΠΈΡΠΎΡΡ Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½Π½ΡΡ
ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ² ΠΊΠ°ΠΏΠΈΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ° ΡΠΎΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠ°ΡΡΡ Π²Π°Π»ΠΎΠ²ΠΎΠ³ΠΎ Π²Π½ΡΡΡΠ΅Π½Π½Π΅Π³ΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΠ°, ΠΈ ΠΎΡ Π΅Π³ΠΎ ΠΎΠ±ΡΠ΅ΠΌΠ° ΠΈ ΡΠ΄Π΅Π»ΡΠ½ΠΎΠ³ΠΎ Π²Π΅ΡΠ° Π² ΡΠΎΡΡΠ°Π²Π΅ ΠΠΠ ΠΌΠΎΠΆΠ½ΠΎ ΡΡΠ΄ΠΈΡΡ ΠΎ ΠΌΠ°ΡΡΡΠ°Π±Π°Ρ
Π²ΠΎΡΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π² ΡΡΡΠ°Π½Π΅.ΠΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡΡ Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π°Ρ
ΠΎΡΠ³Π°Π½ΠΎΠ² Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ, ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΡΡ
ΡΠΎΡΠΈΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ, Π² ΠΊΠΎΡΠΎΡΡΡ
ΡΠ΅ΡΡ ΠΈΠ΄ΡΡ ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π°Ρ
ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, ΡΠ°ΠΊΠΈΡ
ΠΊΠ°ΠΊ ΠΈΠ½Π΄Π΅ΠΊΡΠ½ΡΠΉ, ΡΡΠ΅Π΄Π½ΠΈΡ
Π²Π΅Π»ΠΈΡΠΈΠ½, ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ, Π²ΡΡΡΡΠΎΠ΅Π½ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠΈ Π΄Π»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΡΡΠΎΠΈΠΌΠΎΡΡΠ½ΡΡ
ΠΎΡΠ΅Π½ΠΎΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ², ΠΈΠΌΠ΅ΡΡΠΈΡ
Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠΉ Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½Π½ΡΠΉ ΠΈΠ·Π½ΠΎΡ. ΠΠΎ ΡΠΈΡ
ΠΏΠΎΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ² Π½ΠΎΡΠΈΡ Π»ΠΈΡΡ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠ°ΡΠ½ΡΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ. ΠΡΠΎ ΠΊΠ°ΡΠ°Π΅ΡΡΡ ΠΊΠ°ΠΊ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π·Π°ΠΊΠΎΠ½ΠΎΠ΄Π°ΡΠ΅Π»ΡΡΡΠ²Π° (Π€Π΅Π΄Π΅ΡΠ°Π»ΡΠ½ΡΠΉ Π·Π°ΠΊΠΎΠ½ β 135 Β«ΠΠ± ΠΎΡΠ΅Π½ΠΎΡΠ½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈΒ» ΠΎΡ 16.07.1998 Π³. Π² ΡΠ΅Π΄Π°ΠΊΡΠΈΠΈ 05.07.2016 Π³.), ΡΠ°ΠΊ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΎΠ² ΠΈ ΡΠ΅Π³Π»Π°ΠΌΠ΅Π½ΡΠΎΠ² ΠΎΡΠ΅Π½ΠΎΡΠ½ΠΎ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ, Π‘ΡΠ°Π½Π΄Π°ΡΡΡ ΠΎΡΠ΅Π½ΠΎΡΠ½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ. ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠΎΠ±ΠΎΠΉ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ Π±Π°Π·Ρ Π ΠΎΡΡΡΠ°ΡΠ°, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΡΠΌ ΠΎΠ±ΡΠ΅ΠΊΡΠ°ΠΌ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ², ΡΡΠ°Π²Π½Π΅Π½ΠΈΠ΅ Π΄ΠΎΠ»ΠΆΠ½ΠΎ Π²Π΅ΡΡΠΈΡΡ ΠΈΠΌΠ΅Π½Π½ΠΎ Π² Π³ΡΠ°Π½ΠΈΡΠ°Ρ
ΡΠΎΠΉ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ Π³ΡΡΠΏΠΏΡ, ΠΊ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΡΠ΅ΡΡΡ Π΄Π°Π½Π½ΡΠΉ ΠΎΠ±ΡΠ΅ΠΊΡ.ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΏΡΠΈ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π·Π°ΡΡΠ°ΡΠ½ΠΎΠ³ΠΎ ΠΈ ΡΡΠ°Π²Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² Π² ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠ°Ρ, Π²ΡΡΡΡΠΏΠ°ΡΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠΌ Π½Π°ΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΠ΄Π½ΠΈΡ
ΡΠΎΠ»ΡΠΊΠΎ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΎΠΊ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΎΡΠ΅Π½ΠΎΡΠ½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ Π² ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΡΠ½ΠΊΠ° ΠΈ Π½Π°ΡΡΠ½ΠΎ-ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ Π΄Π»Ρ ΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ Π²ΡΠ΅Ρ
ΠΈΠΌΠ΅ΡΡΠΈΡ
ΡΡ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΡΠ΅ΡΡΡΡΠΎΠ² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ ΠΈ ΠΈΡ
ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΠ³ΠΎ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»Π°. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°ΠΏΠΏΠ°ΡΠ°ΡΠ°, ΡΠ°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡΡ Π΄Π»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΠΎΠ±ΠΎΠ±ΡΠ°ΡΡΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ² Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΠΎΠ³Π°ΡΡΡΠ²Π° ΡΡΡΠ°Π½Ρ.Π Π·Π°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠΈ ΡΠ»Π΅Π΄ΡΠ΅Ρ ΠΎΡΠΌΠ΅ΡΠΈΡΡ, ΡΡΠΎ ΡΠ΅ΡΡ ΠΌΠΎΠΆΠ΅Ρ ΠΈΠ΄ΡΠΈ ΠΎ ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π°Ρ
, Π²ΡΡΡΡΠ°ΠΈΠ²Π°Π½ΠΈΠΈ ΡΠΈΠΏΠΎΠ²ΡΡ
Π°Π»Π³ΠΎΡΠΈΡΠΌΠΎΠ² ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΏΡΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΈ ΠΎΠ±ΠΎΠ·Π½Π°ΡΠ΅Π½Π½ΠΎΠΉ Π½Π°ΡΡΠ½ΠΎ-ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ, Π² Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠΈ ΠΎΡ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΏΡΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ½ΠΎΡΡΠΈ ΠΎΡΠ΅Π½ΠΈΠ²Π°Π΅ΠΌΡΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ². ΠΠΎΠ²ΠΎΡΠΈΡΡ ΠΎ ΡΠΎΡΠΌΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ², ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π»ΠΈΡΡ Π±Ρ, Π½Π΅ΠΊΡΡ ΠΎΡΡΠ΅ΡΠ½ΠΎΡΡΡ ΠΏΡΠ΅ΠΆΠ΄Π΅Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ. ΠΠ»Ρ ΡΡΠΎΠ³ΠΎ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ Π²ΠΎΠΏΡΠΎΡΠ° ΠΎ ΠΏΠ΅ΡΠ΅ΠΏΠΈΡΠΈ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΡΠ΅Π΄ΡΡΠ², Ρ
ΠΎΡΡ Π±Ρ Π½Π° ΡΡΠΎΠ²Π½Π΅ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² β ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ
Optoacoustic solitons in Bragg gratings
Optical gap solitons, which exist due to a balance of nonlinearity and
dispersion due to a Bragg grating, can couple to acoustic waves through
electrostriction. This gives rise to a new species of ``gap-acoustic'' solitons
(GASs), for which we find exact analytic solutions. The GAS consists of an
optical pulse similar to the optical gap soliton, dressed by an accompanying
phonon pulse. Close to the speed of sound, the phonon component is large. In
subsonic (supersonic) solitons, the phonon pulse is a positive (negative)
density variation. Coupling to the acoustic field damps the solitons'
oscillatory instability, and gives rise to a distinct instability for
supersonic solitons, which may make the GAS decelerate and change direction,
ultimately making the soliton subsonic.Comment: 5 pages, 3 figure
Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ Π΄Π»Ρ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΈ ΡΡΡΡΠΊΡΡΡΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Statistical study of the primary real estate market is always associated with the problem that the object is in a constant, and very intense change, both in quantitative terms and in its internal content. Therefore, the issues of constant adaptation of statistical methodology in relation to the primary real estate market are relevant continuously. Among the tasks that are constantly in the field of statistical science and practice in relation to the primary real estate market are the following. First, a critical analysis of the content of the modern primary real estate market, which should allow to identify its fundamental features as an object of statistical research, to systematize the economic relations of the subjects of this market segment for a comprehensive statistical analysis of its functioning and development in any region of Russia. Secondly, it is the construction of analytical classifications of the primary real estate market, systematization of criteria for their construction, which should allow for a qualitative analysis of the structure of this market segment in the modern market economy. Third, the continuous improvement of the system of statistical indicators of the primary real estate market, whichΒ should be constantly supplemented by various blocks of indicators, the use of which will link the development of the primary real estate market with indicators of the standard of living of the population and socio-economic development of a particular region on the basis of the formation and ordering of its various subsystems, which will increase their consistency with indicators of living standards and socio-economic development. To Develop the theory and statistical methodology of the complex study of the primary real estate market in terms of the development of criteria for the division of the object into homogeneous groups by typological characteristics and the construction on their basis of statistical classifications necessary for the structural analysis of the primary real estate market. To obtain scientific results in this article, General scientific methods of cognition, such as scientific abstraction, analysis and synthesis, are used, since it is a question of dividing a single whole into typologically homogeneous complexes, the organic relationship between which ensures the integrity and unity of the studied object β the primary real estate market. In addition, the use of the statistical grouping method is considered throughout the work, as it is an applied application of typological criteria. The main classification features of economic assets traded in the primary real estate market of the region are Substantiated and formulated. The development of criteria for the typological division of the object allowed to build statistical classifications necessary for a comprehensive analysis of the structure and structural changes in the primary real estate market. In the scientific article deals with the problematic aspects of a statistical study of the primary real estate market in parts of its etymology on the basis of clear criteria against which to understand the quality and properties of the traded on its economic assets, to build a statistical classification. All this is a step in the first stage of the statistical study in the sequence that is classically considered by the General theory of statistics. Statistical classifications and groupings by typological features precede the science-intensive substantiation and application of complex mathematical and static methods for factor analysis and forecasting of primary real estate market indicators.Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π²ΡΠ΅Π³Π΄Π° ΡΠΎΠΏΡΡΠΆΠ΅Π½ΠΎ Ρ ΡΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΎΠΉ, ΡΡΠΎ ΠΎΠ±ΡΠ΅ΠΊΡ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡΡ Π² ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΌ, ΠΏΡΠΈΡΡΠΌ Π²Π΅ΡΡΠΌΠ° ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΠΌ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΈ, ΠΊΠ°ΠΊ Π² ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌ Π°ΡΠΏΠ΅ΠΊΡΠ΅, ΡΠ°ΠΊ ΠΈ Π² ΡΠ²ΠΎΡΠΌ Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΌ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠΈ. ΠΠΎΡΡΠΎΠΌΡ ΠΈ Π²ΠΎΠΏΡΠΎΡΡ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΉ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π°ΠΊΡΡΠ°Π»ΡΠ½Ρ Π½Π΅ΠΏΡΠ΅ΡΡΠ²Π½ΠΎ. Π‘ΡΠ΅Π΄ΠΈ Π·Π°Π΄Π°Ρ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ Π½Π°Ρ
ΠΎΠ΄ΡΡΡΡ Π² ΠΏΠΎΠ»Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°ΡΠΊΠΈ ΠΈ ΠΏΡΠ°ΠΊΡΠΈΠΊΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΌΠΎΠΆΠ½ΠΎ Π²ΡΠ΄Π΅Π»ΠΈΡΡ ΡΠ»Π΅Π΄ΡΡΡΠΈΠ΅. ΠΠΎ-ΠΏΠ΅ΡΠ²ΡΡ
, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΊΡΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΡΠΎ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡΡ Π²ΡΡΠ²ΠΈΡΡ Π΅Π³ΠΎ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΈΠ°Π»ΡΠ½ΡΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΡΠ·ΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ½ΠΊΠ° Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π΅Π³ΠΎ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π² Π»ΡΠ±ΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π ΠΎΡΡΠΈΠΈ. ΠΠΎ-Π²ΡΠΎΡΡΡ
, ΡΡΠΎ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΈΡ
ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ, ΡΡΠΎ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡΡ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΡΡΡΠΊΡΡΡΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ½ΠΊΠ° Π² ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. Π-ΡΡΠ΅ΡΡΠΈΡ
, ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠ΅ ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ Π΄ΠΎΠ»ΠΆΠ½Π° Π΄ΠΎΠΏΠΎΠ»Π½ΡΡΡΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌΠΈ Π±Π»ΠΎΠΊΠ°ΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ ΡΠ²ΡΠ·Π°ΡΡ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΈΠΎΠ½Π° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π΅Π΅ ΠΏΠΎΠ΄ΡΠΈΡΡΠ΅ΠΌ, ΡΡΠΎ ΠΏΠΎΠ²ΡΡΠΈΡ ΠΈΡ
ΡΠΎΠ³Π»Π°ΡΠΎΠ²Π°Π½Π½ΠΎΡΡΡ Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ. Π¦Π΅Π»Ρ: Π Π°Π·Π²ΠΈΡΠΈΠ΅ ΡΠ΅ΠΎΡΠΈΠΈ ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² ΡΠ°ΡΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° Π½Π° ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ ΠΏΠΎ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ Π½Π° ΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΡ
Π΄Π»Ρ ΡΡΡΡΠΊΡΡΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΠ»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ Π½Π°ΡΡΠ½ΡΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΎΠ±ΡΠ΅Π½Π°ΡΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ, ΡΠ°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ Π½Π°ΡΡΠ½Π°Ρ Π°Π±ΡΡΡΠ°ΠΊΡΠΈΡ, Π°Π½Π°Π»ΠΈΠ· ΠΈ ΡΠΈΠ½ΡΠ΅Π·, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΡΠ΅ΡΡ ΠΈΠ΄Π΅Ρ ΠΎ ΡΠ°Π·Π±ΠΈΠ΅Π½ΠΈΠΈ Π΅Π΄ΠΈΠ½ΠΎΠ³ΠΎ ΡΠ΅Π»ΠΎΠ³ΠΎ Π½Π° ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ, ΠΎΡΠ³Π°Π½ΠΈΡΠ½Π°Ρ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Ρ ΠΌΠ΅ΠΆΠ΄Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ ΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π΅Ρ ΡΠ΅Π»ΠΎΡΡΠ½ΠΎΡΡΡ ΠΈ Π΅Π΄ΠΈΠ½ΡΡΠ²ΠΎ ΠΈΠ·ΡΡΠ°Π΅ΠΌΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ° β ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π½Π° ΠΏΡΠΎΡΡΠΆΠ΅Π½ΠΈΠΈ Π²ΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΎΠΊ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΡΠ΅ΡΡ ΠΈΠ΄Π΅Ρ ΠΎ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΠΌ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π΅Π΄ΠΈΠ½ΠΈΡ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ Π² ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Ρ ΠΈ ΡΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΎΠ±ΡΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°. Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»Π° ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΠ΅ Π΄Π»Ρ Π²ΡΠ΅ΡΡΠΎΡΠΎΠ½Π½Π΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΡΡΡΠΊΡΡΡΡ ΠΈ ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΡΠ΄Π²ΠΈΠ³ΠΎΠ² Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅: Π Π½Π°ΡΡΠ½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ½ΡΠ΅ Π°ΡΠΏΠ΅ΠΊΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² ΡΠ°ΡΡΠΈ Π΅Π³ΠΎ ΡΡΠΈΠΌΠΎΠ»ΠΎΠ³ΠΈΠ·Π°ΡΠΈΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΡΠΊΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π², ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΡ
ΠΏΠΎΠ½ΡΡΡ ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΠΎΠ±ΡΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ Π½Π° Π½Π΅ΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ. ΠΡΡ ΡΡΠΎ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π³ΠΎΠΌ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΏΠ΅ΡΠ²ΠΎΠ³ΠΎ ΡΡΠ°ΠΏΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΠΎΠΉ Π΅Π³ΠΎ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΎΠ±ΡΠ΅ΠΉ ΡΠ΅ΠΎΡΠΈΠ΅ΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ. Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΊΠΈ ΠΏΠΎ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΏΡΠ΅Π΄ΡΠ΅ΡΡΠ²ΡΡΡ Π½Π°ΡΠΊΠΎΠ΅ΠΌΠΊΠΎΠΌΡ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΡΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Theory of modulational instability in Bragg gratings with quadratic nonlinearity
Modulational instability in optical Bragg gratings with a quadratic nonlinearity is studied. The electric field in such structures consists of forward and backward propagating components at the fundamental frequency and its second harmonic. Analytic continuous wave (CW) solutions are obtained, and the intricate complexity of their stability, due to the large number of equations and number of free parameters, is revealed. The stability boundaries are rich in structures and often cannot be described by a simple relationship. In most cases, the CW solutions are unstable. However, stable regions are found in the nonlinear Schrodinger equation limit, and also when the grating strength for the second harmonic is stronger than that of the first harmonic. Stable CW solutions usually require a low intensity. The analysis is confirmed by directly simulating the governing equations. The stable regions found have possible applications in second-harmonic generation and dark solitons, while the unstable regions maybe useful in the generation of ultrafast pulse trains at relatively low intensities. [S1063-651X(99)03005-6]
Theory of multidimensional parametric band-gap simultons
Multidimensional spatiotemporal parametric simultons (simultaneous solitary waves) are possible in a nonlinear chi((2)) medium with a Bragg grating structure, where large effective dispersion occurs near two resonant band gaps for the carrier and second-harmonic field, respectively. The enhanced dispersion allows much reduced interaction lengths, as compared to bulk medium parametric simultons. The nonlinear parametric band-gap medium permits higher-dimensional stationary waves to form. In addition, solitons can occur with lower input powers than conventional nonlinear Schrodinger equation gap solitons. In this paper, the equations for electromagnetic propagation in a grating structure with a parametric nonlinearity are derived from Maxwell's equation using a coupled mode Hamiltonian analysis in one, two, and three spatial dimensions. Simultaneous solitary wave solutions are proved to exist by reducing the equations to the coupled equations describing a nonlinear parametric waveguide, using the effective-mass approximation (EMA). Exact one-dimensional numerical solutions in agreement with the EMA solutions are also given. Direct numerical simulations show that the solutions have similar types of stability properties to the bulk case, providing the carrier waves are tuned to the two Bragg resonances, and the pulses have a width in frequency space less than the band gap. In summary, these equations describe a physically accessible localized nonlinear wave that is stable in up to 3 + 1 dimensions. Possible applications include photonic logic and switching devices. [S1063-651X(98)06109-1]
Electrically stimulated light-induced second-harmonic generation in glass: evidence of coherent photoconductivity
A strong electrostatic field applied to glass is spatially modulated by intense light at frequencies Ο and 2Ο. The phenomenon is explained in terms of photoconductivity being dependent on the relative phase of the light fields at different frequencies
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