Publications

Neurons in macaque area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture, but it is unknown how selectivity for these features is built from V1 inputs tuned more simply for orientation and spatial frequency. We have recently developed an image-computable two-layer linear-nonlinear network that captures higher-order tuning from a sparse combination of subunits tuned in orientation and scale. This model can be independently trained to predict data from single-unit recordings of V1 and V2 neurons from the awake macaque, responding to a stimulus set comprised of multiple superimposed grating patches that localize oriented contrast energy. These optimized models accurately predict neural responses to other stimuli, including gratings and synthetic textures with higher-order features common to natural images. However, the high-dimensional parameter space of these models makes them difficult to interpret. A systematic comparison of V1 and V2 selectivity is therefore elusive. To address this limitation, we investigate neural tuning across our population of models in silico using local spectral reverse correlation (LSRC; Nishimoto et al., 2006). Here, we present thousands of ternary white noise stimuli to fitted models, computing a response-weighted windowed frequency spectrum across image coordinates. LSRC can effectively characterize the tuning properties of our model neurons, thereby estimating the linear and nonlinear components of model receptive fields. These estimates are qualitatively similar to our direct LSRC measurements made using identical methods from single-unit V1 and V2 recordings collected in separate experiments.

In this work we investigate anharmonic vibrational polaritons formed due to strong light-matter interactions in an optical cavity between radiation modes and anharmonic vibrations beyond the long-wavelength limit. We introduce a conceptually simple description of light-matter interactions, where spatially localized cavity radiation modes couple to localized vibrations. Within this theoretical framework, we employ self-consistent phonon theory and vibrational dynamical mean-field theory to efficiently simulate momentum-resolved vibrational-polariton spectra, including effects of anharmonicity. Numerical simulations in model systems demonstrate the accuracy and applicability of our approach.

We present a new complexification scheme based on the classical double layer potential for the solution of the Helmholtz equation with Dirichlet boundary conditions in compactly perturbed half-spaces in two and three dimensions. The kernel for the double layer potential is the normal derivative of the free-space Green's function, which has a well-known analytic continuation into the complex plane as a function of both target and source locations. Here, we prove that - when the incident data are analytic and satisfy a precise asymptotic estimate - the solution to the boundary integral equation itself admits an analytic continuation into specific regions of the complex plane, and satisfies a related asymptotic estimate (this class of data includes both plane waves and the field induced by point sources). We then show that, with a carefully chosen contour deformation, the oscillatory integrals are converted to exponentially decaying integrals, effectively reducing the infinite domain to a domain of finite size. Our scheme is different from existing methods that use complex coordinate transformations, such as perfectly matched layers, or absorbing regions, such as the gradual complexification of the governing wavenumber. More precisely, in our method, we are still solving a boundary integral equation, albeit on a truncated, complexified version of the original boundary. In other words, no volumetric/domain modifications are introduced. The scheme can be extended to other boundary conditions, to open wave guides and to layered media. We illustrate the performance of the scheme with two and three dimensional examples.

Fixational eye movements alter the number and timing of spikes transmitted from the retina to the brain, but whether these changes enhance or degrade the retinal signal is unclear. To quantify this, we developed a Bayesian method for reconstructing natural images from the recorded spikes of hundreds of retinal ganglion cells (RGCs) in the macaque retina (male), combining a likelihood model for RGC light responses with the natural image prior implicitly embedded in an artificial neural network optimized for denoising. The method matched or surpassed the performance of previous reconstruction algorithms, and provides an interpretable framework for characterizing the retinal signal. Reconstructions were improved with artificial stimulus jitter that emulated fixational eye movements, even when the eye movement trajectory was assumed to be unknown and had to be inferred from retinal spikes. Reconstructions were degraded by small artificial perturbations of spike times, revealing more precise temporal encoding than suggested by previous studies. Finally, reconstructions were substantially degraded when derived from a model that ignored cell-to-cell interactions, indicating the importance of stimulus-evoked correlations. Thus, fixational eye movements enhance the precision of the retinal representation.

We augment the `QUAsi-symmetric Stellarator Repository' (QUASR) to include vacuum field stellarators with quasihelical symmetry using a globalized optimization workflow. The database now has almost 370,000 quasisaxisymmetry and quasihelically symmetric devices along with coil sets, optimized for a variety of aspect ratios, rotational transforms, and discrete rotational symmetries. This paper outlines a couple of ways to explore and characterize the data set. We plot devices on a near-axis quasisymmetry landscape, revealing close correspondence to this predicted landscape. We also use principal component analysis to reduce the dimensionality of the data so that it can easily be visualized in two or three dimensions. Principal component analysis also gives a mechanism to compare the new devices here to previously published ones in the literature. We are able to characterize the structure of the data, observe clusters, and visualize the progression of devices in these clusters. These techniques reveal that the data has structure, and that typically one, two or three principal components are sufficient to characterize it. QUASR is archived at this https URL and can be explored online at this http URL.

The application of an external, oriented electric field has emerged as an attractive technique for manipulating chemical reactions. Because most applications occur in solution, a theory of electric field catalysis requires treatment of the solvent, whose interaction with both the external field and the reacting species modifies the reaction energetics and thus the reaction rate. Here, we formulate such a transition state theory using a dielectric continuum model, and we incorporate dynamical effects due to solvent motion via Grote–Hynes corrections. We apply our theory to the Menshutkin reaction between CH3I and pyridine, which is catalyzed by polar solvents, and to the symmetric SN2 reaction of F– with CH3F, which is inhibited by polar solvents. At low applied field strengths when the solvent responds linearly, our theory predicts near-complete quenching of electric field catalysis. However, a qualitative treatment of the nonlinear response (i.e., dielectric saturation) shows that catalysis can be recovered at appreciable field strengths as solvent molecules begin to align with the applied field direction. The dynamical correction to the rate constant is seen to vary nonmonotonically with increasing solvent polarity due to contrasting effects of the screening ability and the longitudinal relaxation time of the solvent.

We study the interplay between intrinsic topological order and superconductivity in a two-component Haldane bilayer, where the two layers are coupled by an attractive force. We obtain the phase diagram of the model with exact diagonalization in finite size, and develop arguments to assess the stability of the observed phases in the thermodynamic limit. Our main result is that a finite critical attraction strength is needed to pair fermions forming a fractional topological order. This behavior can be harnessed to create clean interfaces between a fractional topological insulator and a superconductor by gating, wherein non-Abelian parafermionic modes are trapped. We discuss realization of such interfaces in the bulk of double bilayers of transition metal dichalcogenides by inhomogenous electrostatic gating, which should mitigate the spurious effects of disorder and crystalline defects present on physical edges.

The phase diagrams of quasi two-dimensional organic superconductors display a plethora of fundamental phenomena associated with strong electron correlations, such as unconventional superconductivity, metal-insulator transitions, frustrated magnetism and spin liquid behavior. We analyze a minimal model for these compounds, the Hubbard model on an anisotropic triangular lattice, using cutting-edge quantum embedding methods respecting the lattice symmetry. We demonstrate the existence of unconventional superconductivity by directly entering the symmetry-broken phase. We show that the crossover from the Fermi liquid metal to the Mott insulator is associated with the formation of a pseudogap. The predicted momentum-selective destruction of the Fermi surface into hot and cold regions provides motivation for further spectroscopic studies. Our results are in remarkable agreement with experimental phase diagrams of κ-BEDT organics.

It has been reported that upon doping a Mott insulator, there can be a crossover to a pseudogaped metallic phase followed by a first-order transition to another thermodynamically stable metallic phase. We call this first-order metal-metal transition the Sordi transition. It was argued that the initial reports of Sordi transitions at finite temperature could be explained by finite size effects and biases related to the model and method used. In this work, we report the Sordi transition on larger clusters at finite temperature on a triangular lattice, where long-range antiferromagnetic fluctuations are frustrated, using a different method, the dynamical cluster approximation instead of the cellular dynamical mean-field theory. This demonstrates that this first-order transition is a directly observable transition in doped Mott insulators and that it is relevant for experiments on candidate spin-liquid organic materials.

Parametric resonances and amplification have led to extraordinary photoinduced phenomena in pump-probe experiments. While these phenomena manifest themselves in out-of-equilibrium settings, here, we present the striking result of parametric amplification in equilibrium. In particular, we demonstrate that quantum and thermal fluctuations of a Raman-active mode amplifies light inside a cavity, at equilibrium, when the Raman mode frequency is twice the cavity mode frequency. This noise-driven amplification leads to the creation of an unusual parametric Raman polariton, intertwining the Raman mode with cavity squeezing fluctuations, with smoking gun signatures in Raman spectroscopy. In the resonant regime, we show the emergence of not only quantum light amplification but also localization and static shift of the Raman mode. Apart from the fundamental interest of equilibrium parametric amplification our study suggests a resonant mechanism for controlling Raman modes and thus matter properties by cavity fluctuations. We conclude by outlining how to compute the Raman-cavity coupling, and suggest possible experimental realization