Past Events

Uncertainty Relations for Metrology and Computation

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Abstract: Uncertainty relations are a familiar part of any introductory quantum mechanics course. In this talk, I will summarize how uncertainty relations have been re-interpreted and re-expressed in the language of information theory, leading to connections with the geometry of quantum state space and the limits of computational and information processing efficiency.

TBA

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Butcher Auditorium, A115, JSCBB 3415 Colorado Ave, Boulder, CO 80303

DART mission: Deflecting an Asteroid by Kinetic Impact

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NASA’s Double Asteroid Redirection Test (DART) mission, the first planetary defense test mission, deliberately impacted an asteroid in order to change its orbit. By impacting Dimorphos, the secondary member of the Didymos near-Earth asteroid binary system, on 2022 September 26, DART demonstrated asteroid deflection by kinetic impact as a technique that may someday be needed to protect the Earth from an asteroid impact threat. Months of subsequent Earth-based observations of the Didymos system showed that the DART impact changed the binary orbital period by –33 min.

Rapid Diagnostics for Infectious Diseases Using Gold Nanoparticles

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Abstract: The global COVID-19 pandemic has underscored the need for innovations in disease diagnostics.  Paper immunoassays, such as lateral flow assays, have been a critical tool for infectious diseases. These assays are low-cost, can be used in rugged environments, and possess sample-to-answer times of minutes, so they are attractive for widespread deployment for disease surveillance, quarantining, and treatment.  Biological fluids such as blood or saliva is added to the paper strip, which wicks through.

Study of Atmospheric Ion Escape From Exoplanet TOI-700 d: Venus Analogs

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Abstract: The recent discovery of Earth-sized planets in the habitable zones (HZ) of cool stars (M dwarfs) has focused attention on whether liquid water and life exist on these planets. These planets are exposed to stronger X-ray and EUV (XUV) radiation than the Solar system terrestrial planets because the X-ray to bolometric luminosity ratio of M dwarfs is substantially larger than Sun-like stars. TOI-700 system is one such target, with an Earth-sized planet (TOI-700 d) in the HZ of the M2 star.

Designing sensors with tensioned silicon nitride micromechanical resonators

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Abstract: Mechanical resonators based on stressed silicon nitride have both exemplary optical and mechanical properties. Through targeted shaping of the resonator geometry, the dissipative properties of these resonators can be enhanced, yielding micromechanical devices that maintain coherence for up to billions of oscillation periods.

TBA

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Butcher Auditorium, A115, JSCBB 3415 Colorado Ave, Boulder, CO 80303

Programmable arrays of alkaline earth atoms: qubits, clocks, and the Bose-Hubbard model

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Abstract: Neutral atoms trapped in optical tweezer arrays have emerged as a promising platform for quantum computing, and for the analog simulation of various spin models. In this work, we apply the programmable control provided by optical tweezer arrays to new domains in quantum science by means of interfacing optical tweezers with a Hubbard-regime optical lattice, and extending the optical tweezer toolbox to new atomic species (namely alkaline earth atoms).

Pushing LIGO’s quantum limits

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Abstract: The Advanced LIGO detectors operate at a regime where quantum uncertainty imposes a fundamental limitation to sensitivity in the form of quantum shot noise and quantum radiation pressure noise. During the last gravitational wave observing run O3, the LIGO and Virgo detectors used quantum states of light known as squeezed states of light in order to reduce high frequency quantum shot noise.

Galaxies in the Making: Recent Advances in Understanding the Star Formation Histories of Galaxie

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Star formation histories (SFHs) encode the rich and complex evolution of galaxies over cosmic time. In recent years, we have made significant progress in understanding SFHs, thanks to a combination of new observational data, theoretical insights, and advances in machine learning.

More than physics, more than data: Integrated machine-learning models for chemistry

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Abstract: Machine-learning techniques are often applied to perform "end-to-end" predictions, that is to make a black-box estimate of a property of interest using only a coarse description of the corresponding inputs.
In contrast, atomic-scale modeling of matter is most useful when it allows to gather a mechanistic insight into the microscopic processes that underlie the behavior of molecules and materials. 

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