This new initiative aims to strengthen connections between Mila’s research community, its partners, and AI experts across Quebec and Canada through in-person meetings and events focused on AI adoption in industry.
Mila is hosting its first quantum computing hackathon on November 21, a unique day to explore quantum and AI prototyping, collaborate on Quandela and IBM platforms, and learn, share, and network in a stimulating environment at the heart of Quebec’s AI and quantum ecosystem.
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Precise radial velocity (pRV) measurements of M-dwarfs in the near-infrared (NIR) rely on empirical templates due to the lack of accurate st… (see more)ellar spectral models in this regime. Templates are assumed to approximate the true spectrum when constructed from many observations or in the high signal-to-noise limit. We develop a numerical simulation that generates SPIRou-like pRV observations from PHOENIX spectra, constructs empirical templates, and estimates radial velocities. This simulation solely considers photon noise and evaluates when empirical templates remain reliable for pRV analysis. Our results reveal a previously unrecognized noise source in templates, establishing a fundamental floor for template-based pRV measurements. We find that templates inherently include distortions in stellar line shapes due to imperfect interpolation at the detector's sampling resolution. The magnitude of this interpolation error depends on sampling resolution and RV content. Consequently, while stars with a higher RV content, such as cooler M-dwarfs are expected to yield lower RV uncertainties, their dense spectral features can amplify interpolation errors, potentially biasing RV estimates. For a typical M4V star, SPIRou's spectral and sampling resolution imposes an RV uncertainty floor of 0.5-0.8 m/s, independent of the star's magnitude or the telescope's aperture. These findings reveal a limitation of template-based pRV methods, underscoring the need for improved spectral modeling and better-than-Nyquist detector sampling to reach the next level of RV precision.
Precise radial velocity (pRV) measurements of M dwarfs in the near-infrared rely on empirical templates due to the lack of accurate stellar … (see more)spectral models in this regime. Templates are assumed to approximate the true spectrum when constructed from many observations or in the high signal-to-noise limit. We develop a numerical simulation that generates SpectroPolarimètre InfraRouge (SPIRou)-like pRV observations from PHOENIX spectra, constructs empirical templates, and estimates radial velocities (RVs). This simulation solely considers photon noise and evaluates when empirical templates remain reliable for pRV analysis. Our results reveal a previously unrecognized noise source in templates created from stacking registered observations, establishing a noise floor for such template-based pRV measurements. We find that these templates inherently include distortions in stellar line shapes due to imperfect interpolation at the detector’s sampling resolution. The magnitude of this interpolation error depends on sampling resolution and RV content. Consequently, for stars with higher RV content, such as cooler M dwarfs, interpolation noise has a larger relative impact, making their performance comparable to hotter M dwarfs when using detectors with low sampling. For a typical M4V star, SPIRou’s spectral and sampling resolution imposes an RV uncertainty floor of 0.5–0.8 m s−1, independent of the star’s magnitude or the telescope’s aperture. These findings reveal a limitation of template-based pRV methods, underscoring the need for improved spectral modeling and better-than-Nyquist detector sampling to reach the next level of RV precision.