MIT Center for Theoretical Physics – a Leinweber Institute

The observation of hybrid mesons in photoproduction experiments can provide essential insight into the inner workings of quantum chromodynamics in the strong coupling regime. In particular, the study of final $η^{(\prime)}π$ states is of great interest due to the presence of the lowest lying hybrid candidate with manifestly exotic quantum numbers, the $π_1(1600)$. In this work, a double-vector exchange model with Reggeized $ρ$ and $ω$ trajectories is developed to describe the photoproduction of $η^{(\prime)}π$ in the high-mass region. Results are presented for the differential cross sections and forward-backward asymmetries in the energy region of interest to the GlueX experiment. The model contains no free parameters, and reproduces the magnitude and $t$-dependence of existing CLAS data at $E_γ=5$\gev. The model predicts a stronger asymmetry in the $η^\prime π$ channel than in the $ηπ$ channel, consistent with what has previously been observed in pion beam experiments. This suggests that the sizeable production of exotic odd waves in $η’π$ is not necessarily related to the presence of gluon-rich environments. Confirmation of these predicted asymmetries from forthcoming GlueX data would enable further predictions of the low-energy spectrum.

We study heat conduction and momentum transport in the context of stochastic fluid dynamics. We consider a fluid described by model H in the classification of Hohenberg and Halperin. We study both non-critical and critical fluids, and we investigate transport properties in two as well as three dimensions. Our results are based on numerical simulations of model H using a Metropolis algorithm, and we employ Kubo relations to extract transport coefficients. We observe the expected logarithmic divergence of the shear viscosity in a two-dimensional non-critical fluid. At a critical point, we find that the transport coefficients exhibit power-law scaling with the system size $L$. The strongest divergence is seen for the thermal conductivity $κ$ in two dimensions. We find $κ\sim L^{x_κ}$ with $x_κ=1.6\pm 0.1$. The divergence is weaker in three dimensions, $x_κ=1.25 \pm 0.3$, and the scaling exponent for the shear viscosity, $x_η$, is significantly smaller than $x_κ$ in both two and three dimensions.

Gauge theories describe the fundamental forces of nature. However, high-energy dynamics, such as the formation of quark-gluon plasmas, is notoriously difficult to model with classical methods. Quantum simulation offers a promising alternative in this regime, yet experiments have mainly probed low energies. Here, we observe the formation of a ballistic plasma and long-time memory effects in high-energy gauge theory dynamics on a high-precision quantum simulator. Both observations are unexpected, as the initial state – fully filled with particle-antiparticle pairs – was thought to rapidly thermalize. Instead, we find correlations spreading ballistically to long distances and a memory of charge clusters. Our observations cannot be explained by many-body scars, but are captured by a new theory of plasma oscillations between electric field and current operators, persisting all the way to the continuum limit of the (1+1)D Schwinger model, of which we simulate a lattice version. Adapting techniques from quantum optics, we visualize plasma oscillations as rotations of Wigner distributions, leading to a novel set of predictions which we test in experiment and numerics. The new framework encompasses both our scenario and scars, which show up as coherent states of the plasma. The experimental surprises we observe in the high-energy dynamics of a simple gauge theory point to the potential of high-precision quantum simulations of gauge theories for general scientific discovery.

Benchmarking quantum devices is a foundational task for the sustained development of quantum technologies. However, accurate in situ characterization of large-scale quantum devices remains a formidable challenge: such systems experience many different sources of errors, and cannot be simulated on classical computers. Here, we introduce new benchmarking methods based on random circuit sampling (RCS), that substantially extend the scope of conventional approaches. Unlike existing benchmarks that report only a single quantity–the circuit fidelity–our framework extracts rich diagnostic information, including spatiotemporal error profiles, correlated and contextual errors, and biased readout errors, without requiring any modifications of the experiment. Furthermore, we develop techniques that achieve this task without classically intractable simulations of the quantum circuit, by leveraging side information, in the form of bitstring samples obtained from reference quantum devices. Our approach is based on advanced high-dimensional statistical modeling of RCS data. We sharply characterize the information-theoretic limits of error estimation, deriving matching upper and lower bounds on the sample complexity across all regimes of side information. We identify surprising phase transitions in learnability as the amount of side information varies. We demonstrate our methods using publicly available RCS data from a state-of-the-art superconducting processor, obtaining in situ characterizations that are qualitatively consistent yet quantitatively distinct from component-level calibrations. Our results establish both practical benchmarking protocols for current and future quantum computers and fundamental information-theoretic limits on how much can be learned from RCS data.