Fermi’s golden rule in a quantum many-body system

Researchers have mapped a detailed dynamical response diagram for a strongly interacting spin-1/2 Fermi gas, demonstrating the emergence and breakdown of Fermi’s golden rule in how transition probabilities unfold. The work shows that, for weak drives, transition probability increases proportionally to the square of time (t2), followed by an intermediate-time regime consistent with Fermi’s golden rule, and then a long-time non-perturbative regime; however, beyond a threshold coupling strength, Rabi oscillations appear. By measuring the transition probability into an outcoupled internal state as a function of both pulse duration and probe coupling strength, the team established a method for applying linear response theory to the spectroscopy of quantum many-body systems. The study reports that these results offer new insight into interpreting spectroscopic experiments and validating a cornerstone of quantum mechanics.

Transition Rates Linked to Microscopic Properties

An initial acceleration in quantum transitions demonstrates the emergence and breakdown of established models of how light interacts with matter. Researchers probing a strongly interacting spin-1/2 Fermi gas have demonstrated the emergence and breakdown of Fermi’s golden rule, a cornerstone of quantum mechanics linking transition rates to microscopic properties. The team, affiliated with the Department of Physics, Yale University, New Haven, CT, USA; Joint Quantum Institute and Joint Center for Quantum Information and Computer Science, NIST/University of Maryland, College Park, MD, USA; and Yale Quantum Institute, Yale University, New Haven, CT, USA, measured the transition probability into an outcoupled internal state as a function of pulse duration and probe coupling strength. For weak drives, they identify an early time regime where the transition probability increases proportionally to t2, an intermediate-time regime consistent with Fermi’s golden rule, and a long-time non-perturbative regime.

This initial t2 behavior is followed by a period consistent with Fermi’s golden rule, before ultimately giving way to a non-perturbative regime at longer timescales. Beyond a threshold coupling strength, Rabi oscillations appear, indicating a strong, coherent interaction between the probe field and the Fermi gas. Mapping the system’s dynamical response diagram represents a method for applying linear response theory to the spectroscopy of quantum many-body systems. Measurements of transition probability, the likelihood of the Fermi gas shifting to an outcoupled internal state, showed that, for weak drives, the initial acceleration precedes the regime consistent with Fermi’s golden rule. The team systematically mapped the system’s dynamical response diagram, and this mapping revealed that beyond a specific coupling strength, Rabi oscillations emerge.

These oscillations indicate a shift into a non-perturbative regime. This detailed mapping establishes a methodology for applying linear response theory, a powerful tool for analyzing system behavior. Researchers are now charting dynamic responses through precise radio-frequency (RF) field coupling, moving beyond simply confirming existing theory.

This initial acceleration precedes the intermediate-time regime consistent with Fermi’s golden rule, offering a glimpse into the very first moments of quantum excitation. The team systematically mapped this initial acceleration alongside other dynamic regimes.

The transition probability increasing proportionally to t2 precedes the regime consistent with Fermi’s golden rule. The team meticulously mapped the system’s dynamical response diagram by measuring the transition probability into an outcoupled internal state as a function of pulse duration and probe coupling strength, providing a method for applying linear response theory to the spectroscopy of quantum many-body systems.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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