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Representing spectral densities, real-frequency, and real-time Green’s functions of continuous systems by a small discrete set of complex poles is a ubiquitous problem in condensed matter physics, with applications ranging from quantum transport simulations to the simulation of strongly correlated electron systems. This paper introduces a method for obtaining a compact, approximate representation of these functions, based on their parameterization on the real axis and a given approximate precision. We show applications to typical spectral functions and results for structured and unstructured correlation functions of model systems. 

Representing real-time data as a sum of complex exponentials provides a compact form that enables both denoising and extrapolation. As a fully data-driven method, the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm is agnostic to the underlying physical equations, making it broadly applicable to various observables and experimental or numerical setups. In this work, we consider applications of the ESPRIT algorithm primarily to extend real-time dynamical data from simulations of quantum systems. We evaluate ESPRIT's performance in the presence of noise and compare it to other extrapolation methods. We demonstrate its ability to extract information from short-time dynamics to reliably predict long-time behavior and determine the minimum time interval required for accurate results. We discuss how this insight can be leveraged in numerical methods that propagate quantum systems in time, and show how ESPRIT can predict infinite-time values of dynamical observables, offering a purely data-driven approach to characterizing quantum phases. 

Abstract The biggest challenge in using CRISPR technologies, which limits their widespread application in medicine, is off-target effects. These effects could, in principle, be minimized by ensuring that CRISPR is activated primarily in the targeted cells, thereby reducing the likelihood of unintended genetic modifications in non-target tissues. Therefore, the development of a light activatable CRISPR approach to dynamically control gene activation in both space and time would be highly beneficial. A drawback is that the overwhelming majority of recently introduced light activatable CRISPR systems require UV or blue light exposure, severely limiting the penetration depth of light in tissue at which CRISPR can be activated, and, in the case of UV light, raising safety concerns. A small number of systems that activate CRISPR using longer wavelengths are hindered by either slow light activation or issues related to toxicity and biocompatibility of the proposed techniques in humans. To address this, we developed a split-Cas9/dCas9 system in which activation is achieved through a near-infrared photocleavable dimerization complex. This photoactivation method can be safely used in humans in vivo, easily adapted to different split-Cas9/dCas9 systems, and enables rapid, spatially precise light activation across various cell types. 

The data set shared herein is related to the test results of a set aeroelastic experiments, carried out in the wind tunnel of SOH Wind Engineering LLC. in Williston, VT (USA). The dynamic wind response of an aeroelastic super-tall building model with external guy wire support (bracing) was examined. The wind tunnel data are made available to the research community. 

We present a minimal pole method for analytically continuing matrix-valued imaginary frequency correlation functions to the real axis, enabling precise access to off-diagonal elements and thus improving the interpretation of self-energies and susceptibilities in quantum simulations. Traditional methods for matrix-valued analytic continuation tend to be either noise sensitive or make ad hoc positivity assumptions. Our approach avoids these issues via the construction of a compact pole representation with shared poles through exponential fits, expanding upon prior work focused on scalar functions. We test our method across various scenarios, including fermionic and bosonic response functions, with and without noise, and for both continuous and discrete spectra of real materials and model systems. Our findings demonstrate that this technique addresses the shortcomings of existing methodologies, such as artificial broadening and positivity violations. The paper is supplemented with a sample implementation in PYTHON. 

Abstract Advancements in materials synthesis have been key to unveil the quantum nature of electronic properties in solids by providing experimental reference points for a correct theoretical description. Here, we report hidden transport phenomena emerging in the ultraclean limit of the archetypical correlated electron system SrVO₃. The low temperature, low magnetic field transport was found to be dominated by anisotropic scattering, whereas, at high temperature, we find a yet undiscovered phase that exhibits clear deviations from the expected Landau Fermi liquid, which is reminiscent of strange-metal physics in materials on the verge of a Mott transition. Further, the high sample purity enabled accessing the high magnetic field transport regime at low temperature, which revealed an anomalously high Hall coefficient. Taken with the strong anisotropic scattering, this presents a more complex picture of SrVO₃that deviates from a simple Landau Fermi liquid. These hidden transport anomalies observed in the ultraclean limit prompt a theoretical reexamination of this canonical correlated electron system beyond the Landau Fermi liquid paradigm, and more generally serves as an experimental basis to refine theoretical methods to capture such nontrivial experimental consequences emerging in correlated electron systems.