Collaborative Research: Detecting First Light and Reionization of the Universe using Advanced Radio Instrumentation

合作研究:使用先进无线电仪器探测宇宙的第一束光和再电离

基本信息

  • 批准号:
    1609547
  • 负责人:
  • 金额:
    $ 14.89万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-09-15 至 2019-08-31
  • 项目状态:
    已结题

项目摘要

In the Big Bang model, the universe started in a very hot state in which the material was ionized. This is now seen as the Cosmic Microwave Background (CMB) radiation. As the universe expanded, it cooled. At later stages, the first stars formed. These caused the neutral material to be ionized again, in the Epoch of Reionization (EoR). At later times, the limit is set by the ionization caused by the first stars. After the first stars, the first galaxies formed. This is a theoretical scenario, so measurements are needed to provide important details needed. The goal of this project is the first measurement of neutral hydrogen from the EoR. Such a measurement is extremely difficult because of instrumental effects. In addition, this project includes the mentoring of undergraduate, graduate and postdoctoral students. The hands-on training provides a unique introduction to ultra-precise measurements, so this will be an unequaled experience involving instrumentation and data analysis. The goal of this project is the measurement of the hyperfine transition of neutral hydrogen. The history of the universe is traced by redshifts, so higher redshifts correspond to earlier times. The CMB arose at a redshift of about 1000. At redshifts of about 30, the most abundant constituent is neutral atomic hydrogen. The highest measured redshift for a galaxy is about 8. Presumably, at redshifts higher than 8, this material was reionized by stars, during the Epoch of Recombination (EoR). Thus the EoR should be bounded by redshifts 8 and 30. At earlier times the limit to the EoR is set by the recombination of ions caused by the CMB. The EoR allows a look back to a time before the first stars and galaxies formed. Depending on the local physical conditions, the spectral line can be either in absorption against the CMB or in emission. Though a measurement of this line, the state of the universe during the EoR can be determined in more detail. This complements the extensive, ongoing studies of the CMB. The proposers will lower the instrumental effects caused by the large linewidth and the high intensity of foreground radiation. They will accomplish this by constructing an improved receiver with a more uniform response over the range of redshifts studied. In addition they will investigate a dipole design that has a more uniform response. These advances are at the forefront of electronics design, and so require a large number of laboratory tests, each of which is very time-consuming. In addition, the proposers are improving their data reductions to further reduce the effect of systematic errors. The detection of the EoR spectrum will serve to expand our knowledge of the evolution of the universe in a very significant, perhaps transformational, fashion. This will provide an important link between the early stages of the universe, before stars formed, and the present stage. The training of students in the techniques of ultra-precise measurements is unique. The interaction with commercial firms may have wide-ranging implications for the design of much improved test equipment.
在大爆炸模型中,宇宙以一种非常热的状态开始,在该状态下,该材料被电离。现在,这被视为宇宙微波背景(CMB)辐射。 随着宇宙的扩展,它冷却了。在后来的阶段,第一颗恒星形成。这些导致中性物质再次被电离,在电离时期(EOR)。在以后的时间,限制是由第一颗恒星引起的电离设定的。 在第一颗恒星之后,第一个星系形成。这是一个理论上的方案,因此需要进行测量以提供所需的重要细节。 该项目的目的是首次测量来自EOR的中性氢。由于工具效应,这种测量非常困难。此外,该项目还包括对本科,研究生和博士后学生的指导。动手培训为超专有测量提供了独特的介绍,因此这将是一种涉及仪器和数据分析的无与伦比的体验。该项目的目的是测量中性氢的超精细转变。宇宙的历史是由红移所追踪的,因此更高的红移与较早的时间相对应。 CMB以大约1000的红移出现。在大约30的红移时,最丰富的成分是中性原子氢。银河系的最高测量的红移约为8。大概,在重组时期(EOR)期间,在高于8的红移时,该材料是由恒星重离的。因此,EOR应由红移8和30界定。在较早的时间,EOR的极限是由CMB引起的离子的重组设定的。 EOR可以回顾一下第一颗恒星和星系形成之前的时间。根据局部物理条件,光谱线可以吸收对抗CMB或发射。尽管对这一线的测量值,但可以更详细地确定EOR期间的宇宙状态。这补充了CMB的广泛研究。提议者将降低由较大的线宽和前景辐射强度高的仪器效应。他们将通过在研究的红移范围内构建改进的接收器来实现这一目标。此外,他们将研究具有更均匀响应的偶极装设计。这些进步位于电子设计的最前沿,因此需要大量的实验室测试,每个测试都非常耗时。此外,提议者正在改善其数据减少,以进一步减少系统错误的效果。 EOR频谱的检测将有助于扩大我们对宇宙发展的了解,以一种非常重要的,也许是变革性的时尚。这将在宇宙的早期阶段,恒星形成和当前阶段之间提供重要的联系。在超精细测量技术方面对学生的培训是独一无二的。与商业公司的互动可能对改进的测试设备的设计具有广泛的影响。

项目成果

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Colin Lonsdale其他文献

Colin Lonsdale的其他文献

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{{ truncateString('Colin Lonsdale', 18)}}的其他基金

REU Site: Astronomy and Geoscience at the Massachusetts Institute of Technology (MIT) Haystack Observatory
REU 站点:麻省理工学院 (MIT) Haystack 天文台的天文学和地球科学
  • 批准号:
    2243909
  • 财政年份:
    2023
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Standard Grant
REU/RET Site: Radio Science in Astronomy, Geodesy, and Geospace Science at MIT Haystack Observatory
REU/RET 站点:麻省理工学院 Haystack 天文台的天文学、大地测量学和地球空间科学中的无线电科学
  • 批准号:
    1950348
  • 财政年份:
    2020
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Standard Grant
Collaborative Research: EDGES-3: Validating and Refining Global 21cm Measurements of Cosmic Dawn
合作研究:EDGES-3:验证和完善宇宙黎明的全球 21 厘米测量
  • 批准号:
    1909307
  • 财政年份:
    2019
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Standard Grant
REU Site: Astronomy and Informatics at the MIT Haystack Observatory
REU 站点:麻省理工学院海斯塔克天文台的天文学和信息学
  • 批准号:
    1659420
  • 财政年份:
    2017
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Standard Grant
REU Site: Astronomy and Atmospheric Science at MIT Haystack Observatory
REU 站点:麻省理工学院海斯塔克天文台的天文学和大气科学
  • 批准号:
    1156504
  • 财政年份:
    2012
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Continuing Grant
MRI: Development of Radio Array of Portable Interferometric Detectors (RAPID)
MRI:便携式干涉探测器无线电阵列 (RAPID) 的开发
  • 批准号:
    1229036
  • 财政年份:
    2012
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Standard Grant
Advanced Correlation Techniques for Next-Generation Radio Arrays
下一代无线电阵列的先进相关技术
  • 批准号:
    0603971
  • 财政年份:
    2006
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Continuing Grant
ITR/AP: The Low Frequency Array (LOFAR) - A Digital Radio Telescope
ITR/AP:低频阵列 (LOFAR) - 数字射电望远镜
  • 批准号:
    0121164
  • 财政年份:
    2001
  • 资助金额:
    $ 14.89万
  • 项目类别:
    Continuing Grant

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复杂环境下非协作直扩信号检测与参数估计方法研究
  • 批准号:
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Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
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协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
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  • 财政年份:
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协作研究:SaTC:核心:小型:检测和本地化机器学习库中的非功能性漏洞
  • 批准号:
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