Publications

Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain..

Substructures in PPDs, whose ubiquity was unveiled by recent ALMA observations, are widely discussed regarding their possible origins. We carry out global full magnetohydrodynamic (MHD) simulations in axisymmetry, coupled with self-consistent ray-tracing radiative transfer, thermochemistry, and non-ideal MHD diffusivities. The abundance profiles of grains are also calculated based on the global dust evolution calculation, including sintering effects. We found that dust size plays a crucial role in the ring formation around the snow lines of protoplanetary disks (PPDs) through the accretion process. Disk ionization structures and thus tensorial conductivities depend on the size of grains.When grains are significantly larger than PAHs, the non-ideal MHD conductivities change dramatically across each snow line of major volatiles, leading to a sudden change of the accretion process across the snow lines and the subsequent formation of gaseous rings/gaps there. On the other hand,the variations of conductivities are a lot less with only PAH sized grains in disks and then these disks retain smoother radial density profiles across snow lines.

We use theory and numerical computation to determine the shape of an axisymmetric fluid membrane with a resistance to bending and constant area. The membrane connects two rings in the classic geometry that produces a catenoidal shape in a soap film. In our problem, we find infinitely many branches of solutions for the shape and external force as functions of the separation of the rings, analogous to the infinite family of eigenmodes for the Euler buckling of a slender rod. Special attention is paid to the catenoid, which emerges as the shape of maximal allowable separation when the area is less than a critical area equal to the planar area enclosed by the two rings. A perturbation theory argument directly relates the tension of catenoidal membranes to the stability of catenoidal soap films in this regime. When the membrane area is larger than the critical area, we find additional cylindrical tether solutions to the shape equations at large ring separation, and that arbitrarily large ring separations are possible. These results apply for the case of vanishing Gaussian curvature modulus; when the Gaussian curvature modulus is nonzero and the area is below the critical area, the force and the membrane tension diverge as the ring separation approaches its maximum value. We also examine the stability of our shapes and analytically show that catenoidal membranes have markedly different stability properties than their soap film counterparts.

Scattering experiments have revolutionized our understanding of nature. Examples include the discovery of the nucleus, crystallography, and the discovery of the double helix structure of DNA. Scattering techniques differ by the type of the particles used, the interaction these particles have with target materials and the range of wavelengths used. Here, we demonstrate a new 2-dimensional table-top scattering platform for exploring magnetic properties of materials on mesoscopic length scales. Long lived, coherent magnonic excitations are generated in a thin film of YIG and scattered off a magnetic target deposited on its surface. The scattered waves are then recorded using a scanning NV center magnetometer that allows sub-wavelength imaging and operation under conditions ranging from cryogenic to ambient environment. While most scattering platforms measure only the intensity of the scattered waves, our imaging method allows for spatial determination of both amplitude and phase of the scattered waves thereby allowing for a systematic reconstruction of the target scattering potential. Our experimental results are consistent with theoretical predictions for such a geometry and reveal several unusual features of the magnetic response of the target, including suppression near the target edges and gradient in the direction perpendicular to the direction of surface wave propagation. Our results establish magnon scattering experiments as a new platform for studying correlated many-body systems.

Since the early days of Dirac flux quantization, magnetic monopoles have been sought after as a potential corollary of quantized electric charge. As opposed to magnetic monopoles embedded into the theory of electromagnetism, Weyl crystals exhibit Berry flux monopoles in reciprocal parameter space. As a function of crystal momentum, such monopoles locate at the degeneracy point of the Weyl cone. Here, we report momentum-resolved spectroscopic signatures of Berry flux monopoles in TaAs as a paradigmatic Weyl semimetal. We have probed the orbital and spin angular momentum (OAM and SAM) of the Weyl-fermion states by angle-resolved photoemission spectroscopy at bulk-sensitive soft X-ray energies (SX-ARPES) combined with photoelectron spin detection and circular dichroism. Supported by first-principles calculations, our measurements image characteristics of a topologically non-trivial winding of the OAM at the Weyl nodes and unveil a chirality-dependent SAM of the Weyl bands. Our results experimentally visualize the non-trivial momentum-space topology in a Weyl semimetal, promising to have profound implications for the study of quantum-geometric effects in solids.

Coupled-cluster theory with single and double excitations (CCSD) is a promising ab initio method for the electronic structure of three-dimensional metals, for which second-order perturbation theory (MP2) diverges in the thermodynamic limit. However, due to the high cost and poor convergence of CCSD with respect to basis size, applying CCSD to periodic systems often leads to large basis set errors. In a common "composite" method, MP2 is used to recover the missing dynamical correlation energy through a focal-point correction, but the inadequacy of MP2 for metals raises questions about this approach. Here we describe how high-energy excitations treated by MP2 can be "downfolded" into a low-energy active space to be treated by CCSD. Comparing how the composite and downfolding approaches perform for the uniform electron gas, we find that the latter converges more quickly with respect to the basis set size. Nonetheless, the composite approach is surprisingly accurate because it removes the problematic MP2 treatment of double excitations near the Fermi surface. Using the method to estimate the CCSD correlation energy in the combined complete basis set and thermodynamic limits, we find CCSD recovers over 90 percent of the exact correlation energy at r

Markov chain Monte Carlo is a key computational tool in Bayesian statistics, but it can be challenging to monitor the convergence of an iterative stochastic algorithm. In this paper we show that the convergence diagnostic R of Gelman and Rubin (1992) has serious flaws. Traditional R will fail to correctly diagnose convergence failures when the chain has a heavy tail or when the variance varies across the chains. In this paper we propose an alternative rank-based diagnostic that fixes these problems. We also introduce a collection of quantile-based local efficiency measures, along with a practical approach for computing Monte Carlo error estimates for quantiles. We suggest that common trace plots should be replaced with rank plots from multiple chains. Finally, we give recommendations for how these methods should be used in practice.

Many problems in the physical sciences, machine learning, and statistical inference necessitate sampling from a high-dimensional, multi-modal probability distribution. Markov Chain Monte Carlo (MCMC) algorithms, the ubiquitous tool for this task, typically rely on random, reversible, and local updates to propagate configurations of a given system in a way that ensures that generated configurations will be distributed according to a target probability distribution asymptotically. In high-dimensional settings with multiple relevant metastable basins, local approaches require either immense computational effort or intricately designed importance sampling strategies to capture information about, for example, the relative populations of such basins. Here we analyze a framework for augmenting MCMC sampling with nonlocal transition kernels parameterized with generative models known as normalizing flows. We focus on a setting where there is no preexisting data, as is commonly the case for problems in which MCMC is used. Our results emphasize that the implementation of the normalizing flow must be adapted to the structure of the target distribution in order to preserve the statistics of the target at all scales. Furthermore, we analyze the propensity of our algorithm to discover new states and demonstrate the importance of initializing the training with some

Nonuniform fast Fourier transforms dominate the computational cost in many applications including image reconstruction and signal processing. We thus present a general-purpose GPU-based CUDA library for type 1 (nonuniform to uniform) and type 2 (uniform to nonuniform) transforms in dimensions 2 and 3, in single or double precision. It achieves high performance for a given user-requested accuracy, regardless of the distribution of nonuniform points, via cache-aware point reordering, and load-balanced blocked spreading in shared memory. At low accuracies, this gives on-GPU throughputs around $10^9$ nonuniform points per second, and (even including host-device transfer) is typically 4-10$\times$ faster than the latest parallel CPU code FINUFFT (at 28 threads). It is competitive with two established GPU codes, being up to 90$\times$ faster at high accuracy and/or type 1 clustered point distributions. Finally we demonstrate a 6-18$\times$ speedup versus CPU in an X-ray diffraction 3D iterative reconstruction task at $10^{-12}$ accuracy, observing excellent multi-GPU weak scaling up to one rank per GPU. paper talk: https://www.youtube.com/watch?v=PnW6ehMyHxM.

In this work, we calibrate the relationship between Halpha emission and M dwarf ages. We compile a sample of 892 M dwarfs with Halpha equivalent width (HaEW) measurements from the literature that are either co-moving with a white dwarf of known age (21 stars) or in a known young association (871 stars). In this sample we identify 7 M dwarfs that are new candidate members of known associations. By dividing the stars into active and inactive categories according to their HaEW and spectral type (SpT), we find that the fraction of active dwarfs decreases with increasing age, and the form of the decline depends on SpT. Using the compiled sample of age-calibrators we find that HaEW and fractional Halpha luminosity (LHaLbol) decrease with increasing age. HaEW for SpT<M7 decreases gradually up until ~1Gyr. For older ages, we found only two early M dwarfs which are both inactive and seem to continue the gradual decrease. We also found 14 mid-type out of which 11 are inactive and present a significant decrease of HaEW, suggesting that the magnetic activity decreases rapidly after ~1Gyr. We fit LHaLbol versus age with a broken power-law and find an index of -0.11+0.02-0.01 for ages <~776Myr. The index becomes much steeper at older ages however a lack of field age-calibrators leaves this part of the relation far less constrained. Finally, from repeated independent measurements for the same stars we find that 94% of these has a level of HaEW variability <=5A at young ages (<1Gyr).