Publications

We study the superconducting pairing correlations in the ground state of the doped Hubbard model -- in its original form without hopping beyond nearest neighbor or other perturbing parameters -- in two dimensions at intermediate to strong coupling and near optimal doping. The nature of such correlations has been a central question ever since the discovery of cuprate high-temperature superconductors. Despite unprecedented effort and tremendous progress in understanding the properties of this fundamental model, a definitive answer to whether the ground state is superconducting in the parameter regime most relevant to cuprates has proved exceedingly difficult to establish. In this work, we employ two complementary, state-of-the-art many-body computational methods, auxiliary-field quantum Monte Carlo (AFQMC) and density matrix renormalization group (DMRG) methods, deploying the most recent algorithmic advances in each. Systematic and detailed comparisons between the two methods are performed. The DMRG is extremely reliable on small width cylinders, where we use it to validate the AFQMC. The AFQMC is then used to study wide systems as well as fully periodic systems, to establish that we have reached the thermodynamic limit. The ground state is found to be non-superconducting in the moderate to strong coupling regime in the vicinity of optimal hole doping.

Accurate and computationally efficient modeling of systems of interacting electrons is an outstanding problem in theoretical and computational materials science. For materials where strong electronic interactions are primarily of a localized character and act within a subspace of localized quantum states on separate atomic sites (e.g., in transition metal and rare-earth compounds), their electronic behaviors are typically described by the Hubbard model and its extensions. In this work, we describe BoSS (Boson Slave Solver), a software implementation of the slave-boson method appropriate for describing a variety of extended Hubbard models, namely p-d models that include both the interacting atomic sites ("d" states) and non-interacting or ligand sites ("p" states). We provide a theoretical background, a description of the equations solved by BoSS, an overview of the algorithms used, the key input/output and control variables of the software program, and tutorial examples of its use featuring band renormalization in SrVO

Self-diffusion in dense rod suspensions are subject to strong geometric constraints because of steric interactions. This topological effect is essentially anisotropic when rods are nematically aligned with their neighbors, raising considerable challenges in understanding and analyzing their impacts on the bulk physical properties. Via a classical Doi-Onsager kinetic model with the Maier-Saupe potential, we characterize the long-time rotational Brownian diffusivity for dense suspensions of hard rods of finite aspect ratios, based on quadratic orientation autocorrelation functions. Furthermore, we show that the computed nonmonotonic scalings of the diffusivity as a function of volume fraction can be accurately predicted by an alternative tube model in the nematic phase.

The nonlinear optical response of an excitonic insulator coupled to lattice degrees of freedom is shown to depend in strong and characteristic ways on whether the insulating behavior originates primarily from electron-electron or electron-lattice interactions. Linear response optical signatures of the massive phase mode and the amplitude (Higgs) mode are identified. Upon nonlinear excitation resonant to the phase mode, a new in-gap mode at twice the phase mode frequency is induced, leading to a huge second harmonic response. Excitation of in-gap phonon modes leads to different and much smaller effects. A Landau-Ginzburg theory analysis explain these different behavior and reveals that a parametric resonance of the strongly excited phase mode is the origin of the photo-induced mode in the electron-dominant case. The difference in the nonlinear optical response serve as a measure of the dominant mechanism of the ordered phase.

The famous Arrhenius equation is well motivated to describe the temperature dependence of chemical reactions but has also been used for complicated biological processes. Here, we evaluate how well the simple Arrhenius equation predicts complex multistep biological processes, using frog and fruit fly embryogenesis as two canonical models. We find the Arrhenius equation provides a good approximation for the temperature dependence of embryogenesis, even though individual developmental stages scale differently with temperature. At low and high temperatures, however, we observed significant departures from idealized Arrhenius Law behavior. When we model multistep reactions of idealized chemical networks we are unable to generate comparable deviations from linearity. In contrast, we find the single enzyme GAPDH shows non-linearity in the Arrhenius plot similar to our observations of embryonic development. Thus, we find that complex embryonic development can be well approximated by the simple Arrhenius Law and propose that the observed departure from this law results primarily from non-idealized individual steps rather than the complexity of the system.

Dorsal root ganglia (DRG) are promising sites for recording sensory activity. Current technologies for DRG recording are stiff and typically do not have sufficient site density for high-density neural data techniques. We demonstrate neural recordings in feline sacral DRG using a flexible polyimide microelectrode array with 30-40 μm site spacing. We delivered arrays into DRG with ultrananocrystalline diamond shuttles designed for high stiffness with small footprint. We recorded neural activity during sensory activation, including cutaneous brushing and bladder filling. We successfully delivered arrays in 5/6 experiments and recorded sensory activity in 4. Median signal amplitude was 55 μV and the maximum unique units recorded at one array position was 260, with 157 driven by sensory or electrical stimulation. We used specialized high-density neural signal analysis software to sort neural signals and, in one experiment, track 8 signals as the array was retracted 500 μm. This study is the first demonstration of ultrathin, flexible, high-density electronics delivered into DRG, with capabilities for recording and tracking sensory information that are a significant improvement over conventional DRG interfaces.Competing Interest StatementT.M.B. is a named inventors on a granted patent (US9622671B2; assigned to University of Pittsburgh) which is on the monitoring of physiological states via microelectrodes at DRG. The authors declare no other personal or institutional interest with regards to the authorship and/or publication of this manuscript.

The remarkable null pulse coincident with the 2016 glitch in Vela rotation indicates a dynamical event involving the crust and the magnetosphere of the neutron star. We propose that a crustal quake associated with the glitch strongly disturbed the Vela magnetosphere and thus interrupted its radio emission. We present the first global numerical simulations of a neutron starquake. Our code resolves the elasto-dynamics of the entire crust and follows the evolution of Alfvén waves excited in the magnetosphere. We observe Rayleigh surface waves propagating away from the epicenter of the quake, around the circumference of the crust - an instance of the so-called whispering gallery modes. The Rayleigh waves set the initial spatial scale of the magnetospheric disturbance. Once launched, the Alfvén waves bounce in the closed magnetosphere, become de-phased, and generate strong electric currents, capable of igniting electric discharge. Most likely, the discharge floods the magnetosphere with electron-positron plasma, quenching the radio emission. We find that the observed ∼0.2 s disturbance is consistent with the damping time of the crustal waves if the crust is magnetically coupled to the superconducting core of the neutron star. The quake is expected to produce a weak X-ray burst of short duration.

The double-helical topology of DNA molecules observed at room temperature in the absence of any external loads can be disrupted by increasing the bath temperature or by applying tensile forces, leading to spontaneous strand separation known as DNA melting. Here, continuum mechanics of a 2D birod is combined with statistical mechanics to formulate a unified framework for studying both thermal melting and tensile force induced melting of double-stranded molecules: it predicts the variation of melting temperature with tensile load, provides a mechanics-based understanding of the cooperativity observed in melting transitions, and reveals an interplay between solution electrostatics and micromechanical deformations of DNA which manifests itself as an increase in the melting temperature with increasing ion concentration. This novel predictive framework sheds light on the micromechanical aspects of DNA melting and predicts trends that were observed experimentally or extracted phenomenologically using the Clayperon equation.

We investigate the effects of massive black hole growth on the structural evolution of dwarf galaxies within the Romulus25 cosmological hydrodynamical simulation. We study a sample of 228 central, isolated dwarf galaxies with stellar masses Mstar<1010M⊙ and a central BH. We find that the local MBH−Mstar relation exhibits a high degree of scatter below Mstar109M⊙ are more likely to exhibit lower central stellar mass density, lower HI gas content, and lower star formation rates than their undermassive BH counterparts. Our results suggest that overmassive BHs in isolated galaxies above Mstar>109M⊙ are capable of driving feedback, in many cases suppressing and even quenching star formation by late times.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increased exponentially from mid-March to mid-April, after which they began to decline. Viral titers in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral titers as a convolution of back-dated new clinical cases with the viral shedding function of an individual. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. Finally, we found that wastewater viral titers at the neighborhood level correlate better with demographic variables than with population size. This work suggests that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.