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Veit Elser

Publications and source records attributed to Veit Elser.

At least 55 records · Page 3Linked to original sources
arXiv2010

Recovering magnetization distributions from their noisy diffraction data

We study, using simulated experiments inspired by thin film magnetic domain patterns, the feasibility of phase retrieval in X-ray diffractive imaging in the presence of intrinsic charge scattering given only photon-shot-noise limited diffraction data. We detail a reconstruction algorithm to recover the sample's magnetization distribution under such conditions, and compare its performance with that of Fourier transform holography. Concerning the design of future experiments, we also chart out the reconstruction limits of diffractive imaging when photon- shot-noise and the intensity of charge scattering noise are independently varied. This work is directly relevant to the time-resolved imaging of magnetic dynamics using coherent and ultrafast radiation from X-ray free electron lasers and also to broader classes of diffractive imaging experiments which suffer noisy data, missing data or both.

cond-mat.mtrl-sci↗
arXiv2010

A method for dense packing discovery

The problem of packing a system of particles as densely as possible is foundational in the field of discrete geometry and is a powerful model in the material and biological sciences. As packing problems retreat from the reach of solution by analytic constructions, the importance of an efficient numerical method for conducting \textit{de novo} (from-scratch) searches for dense packings becomes crucial. In this paper, we use the \textit{divide and concur} framework to develop a general search method for the solution of periodic constraint problems, and we apply it to the discovery of dense periodic packings. An important feature of the method is the integration of the unit cell parameters with the other packing variables in the definition of the configuration space. The method we present led to improvements in the densest-known tetrahedron packing which are reported in [arXiv:0910.5226]. Here, we use the method to reproduce the densest known lattice sphere packings and the best known lattice kissing arrangements in up to 14 and 11 dimensions respectively (the first such numerical evidence for their optimality in some of these dimensions). For non-spherical particles, we report a new dense packing of regular four-dimensional simplices with density $ϕ=128/219\approx0.5845$ and with a similar structure to the densest known tetrahedron packing.

math.MG↗
arXiv2010

Dense periodic packings of tetrahedra with small repeating units

We present a one-parameter family of periodic packings of regular tetrahedra, with the packing fraction $100/117\approx0.8547$, that are simple in the sense that they are transitive and their repeating units involve only four tetrahedra. The construction of the packings was inspired from results of a numerical search that yielded a similar packing. We present an analytic construction of the packings and a description of their properties. We also present a transitive packing with a repeating unit of two tetrahedra and a packing fraction $\frac{139+40\sqrt{10}}{369}\approx0.7194$.

math.MG↗
arXiv2009

A reconstruction algorithm for single-particle diffraction imaging experiments

We introduce the EMC algorithm for reconstructing a particle's 3D diffraction intensity from very many photon shot-noise limited 2D measurements, when the particle orientation in each measurement is unknown. The algorithm combines a maximization step (M) of the intensity's likelihood function, with expansion (E) and compression (C) steps that map the 3D intensity model to a redundant tomographic representation and back again. After a few iterations of the EMC update rule, the reconstructed intensity is given to the difference-map algorithm for reconstruction of the particle contrast. We demonstrate reconstructions with simulated data and investigate the effects of particle complexity, number of measurements, and the number of photons per measurement. The relatively transparent scaling behavior of our algorithm provides a first estimate of the data processing resources required for future single-particle imaging experiments.

physics.data-an↗
arXiv2008

Laminating lattices with symmetrical glue

We use the automorphism group $Aut(H)$, of holes in the lattice $L_8=A_2\oplus A_2\oplus D_4$, as the starting point in the construction of sphere packings in 10 and 12 dimensions. A second lattice, $L_4=A_2\oplus A_2$, enters the construction because a subgroup of $Aut(L_4)$ is isomorphic to $Aut(H)$. The lattices $L_8$ and $L_4$, when glued together through this relationship, provide an alternative construction of the laminated lattice in twelve dimensions with kissing number 648. More interestingly, the action of $Aut(H)$ on $L_4$ defines a pair of invariant planes through which dense, non-lattice packings in 10 dimensions can be constructed. The most symmetric of these is aperiodic with center density 1/32. These constructions were prompted by an unexpected arrangement of 378 kissing spheres discovered by a search algorithm.

math.MG↗
arXiv2007

Divide and concur: A general approach to constraint satisfaction

Many difficult computational problems involve the simultaneous satisfaction of multiple constraints which are individually easy to satisfy. Such problems occur in diffractive imaging, protein folding, constrained optimization (e.g., spin glasses), and satisfiability testing. We present a simple geometric framework to express and solve such problems and apply it to two benchmarks. In the first application (3SAT, a boolean satisfaction problem), the resulting method exhibits similar performance scaling as a leading context-specific algorithm (walksat). In the second application (sphere packing), the method allowed us to find improved solutions to some old and well-studied optimization problems. Based upon its simplicity and observed efficiency, we argue that this framework provides a competitive alternative to stochastic methods such as simulated annealing.

physics.comp-ph↗
arXiv2007

Noise limits in the assembly of diffraction data

We obtain an information theoretic criterion for the feasibility of assembling diffraction signals from noisy tomographs when the positions of the tomographs within the signal are unknown. For shot-noise limited data, the minimum number of detected photons per tomograph for successful assembly is much smaller than previously believed necessary, growing only logarithmically with the number of resolution elements of the diffracting object. We also demonstrate assembly up to the information theoretic limit with a constraint-based algorithm.

physics.comp-ph↗
arXiv2007

Protein structure prediction by an iterative search method

We demonstrate a new algorithm for finding protein conformations that minimize a non-bonded energy function. The new algorithm, called the difference map, seeks to find an atomic configuration that is simultaneously in two constraint spaces. The first constraint space is the space of atomic configurations that have a valid peptide geometry, while the second is the space of configurations that have a non-bonded energy below a given target. These two constraint spaces are used to define a deterministic dynamical system, whose fixed points produce atomic configurations in the intersection of the two constraint spaces. The rate at which the difference map produces low energy protein conformations is compared with that of a contemporary search algorithm, parallel tempering. The results indicate the difference map finds low energy protein conformations at a significantly higher rate then parallel tempering.

q-bio.BM↗
arXiv2006

The sloppy model universality class and the Vandermonde matrix

In a variety of contexts, physicists study complex, nonlinear models with many unknown or tunable parameters to explain experimental data. We explain why such systems so often are sloppy; the system behavior depends only on a few `stiff' combinations of the parameters and is unchanged as other `sloppy' parameter combinations vary by orders of magnitude. We contrast examples of sloppy models (from systems biology, variational quantum Monte Carlo, and common data fitting) with systems which are not sloppy (multidimensional linear regression, random matrix ensembles). We observe that the eigenvalue spectra for the sensitivity of sloppy models have a striking, characteristic form, with a density of logarithms of eigenvalues which is roughly constant over a large range. We suggest that the common features of sloppy models indicate that they may belong to a common universality class. In particular, we motivate focusing on a Vandermonde ensemble of multiparameter nonlinear models and show in one limit that they exhibit the universal features of sloppy models.

cond-mat.stat-mech↗
arXiv2005

Reconstruction of an object from its symmetry-averaged diffraction pattern

By suitably generalizing the Fourier constraint projection in the difference map phasing algorithm, an object can be reconstructed from its diffraction pattern even when the latter has been incoherently averaged over a discrete group of symmetries. This resolves an ambiguity in the recent proposal for aligning molecules by means of their anisotropic dielectric interaction with an intense light field. The algorithm is demonstrated with simulated data in two and three dimensions.

physics.data-an↗
arXiv2005

Deconstructing the energy landscape: new algorithms for folding heteropolymers

We apply the computational methodology of phase retrieval to the problem of folding heteropolymers. The ground state fold of the polymer is defined by the intersection of two sets in the configuration space of its constituent monomers: a geometrical chain constraint and a threshold constraint on the contact energy. A dynamical system is then defined in terms of the projections to these constraint sets, such that its fixed points solve the set intersection problem. We present results for two off-lattice HP models: one with only rotameric degrees of freedom, and one proposed by Stillinger et al. with flexible bond angles. Our phase retrieval inspired algorithm is competitive with more established algorithms and even finds lower energy folds for one of the longer polymer chains.

q-bio.BM↗
arXiv2003

Bit retrieval: intractability and application to digital watermarking

Bit retrieval, the problem of determining a binary sequence from its cyclic autocorrelation, is a special case of the phase retrieval problem. Algorithms for phase retrieval are extensively used in several scientific disciplines, and yet, very little is known about the complexity of these algorithms or phase retrieval in general. Here we show that bit retrieval, in particular, is closely related to computations that arise in algebraic number theory and can also be formulated as an integer program. We find that general purpose algorithms from these fields, when applied to bit retrieval, are outperformed by a particular iterative phase retrieval algorithm. This algorithm still has exponential complexity and motivates us to propose a new public key signature scheme based on the intractability of bit retrieval, and image watermarking as a possible application.

math.NT↗
arXiv2002

Dynamics of immersed molecules in superfluids

The dynamics of a molecule immersed in a superfluid medium are considered. Results are derived using a classical hydrodynamic approach followed by canonical quantization. The classical model, a rigid body immersed in incompressible fluid, permits a thorough analysis; its effective Hamiltonian generalizes the usual rigid-rotor Hamiltonian. In contrast to the free rigid rotor, the immersed body is shown to have chaotic dynamics. Quantization of the classical model leads to new and experimentally verifiable features. It is shown, for instance, that chiral molecules can behave as "quantum propellers": the rotational-translational coupling induced by the superfluid leads to a nonzero linear momentum in the ground state. Hydrogen peroxide is a strong candidate for experimental detection of this effect. The signature is a characteristic splitting of rotational absorption lines. The 1_{01} --> 1_{10} line in hydrogen peroxide, for example, is predicted to split into three lines separated by as much as 0.01 cm^{-1}, which is about the experimental linewidth.

physics.flu-dyn↗
arXiv2002

Solution of the crystallographic phase problem by iterated projections

An algorithm for determining crystal structures from diffraction data is described which does not rely on the usual Fourier-space formulations of atomicity. The new algorithm implements atomicity constraints in real-space, as well as intensity constraints in Fourier-space, by projections which restore each constraint with the minimal modification of the scattering density. To recover the true density, the two projections are combined into a single operation, the difference map, which is iterated until the magnitude of the density modification becomes acceptably small. The resulting density, when acted upon by a single additional operation, is by construction a density which satisfies both intensity and atomicity constraints. Numerical experiments have yielded solutions for atomic resolution x-ray data sets with over 400 non-hydrogen atoms, as well as for neutron data, where positivity of the density cannot be invoked.

cond-mat↗
arXiv2002

Random projections and the optimization of an algorithm for phase retrieval

Iterative phase retrieval algorithms typically employ projections onto constraint subspaces to recover the unknown phases in the Fourier transform of an image, or, in the case of x-ray crystallography, the electron density of a molecule. For a general class of algorithms, where the basic iteration is specified by the difference map, solutions are associated with fixed points of the map, the attractive character of which determines the effectiveness of the algorithm. The behavior of the difference map near fixed points is controlled by the relative orientation of the tangent spaces of the two constraint subspaces employed by the map. Since the dimensionalities involved are always large in practical applications, it is appropriate to use random matrix theory ideas to analyze the average-case convergence at fixed points. Optimal values of the gamma parameters of the difference map are found which differ somewhat from the values previously obtained on the assumption of orthogonal tangent spaces.

math.NA↗
arXiv2002

The Mermin fixed point

The most efficient known method for solving certain computational problems is to construct an iterated map whose fixed points are by design the problem's solution. Although the origins of this idea go back at least to Newton, the clearest expression of its logical basis is an example due to Mermin. A contemporary application in image recovery demonstrates the power of the method.

nlin.CG↗
arXiv2001

Phase retrieval by iterated projections

Several strategies in phase retrieval are unified by an iterative "difference map" constructed from a pair of elementary projections and a single real parameter $β$. For the standard application in optics, where the two projections implement Fourier modulus and object support constraints respectively, the difference map reproduces the "hybrid" form of Fienup's input-output map for $β= 1$. Other values of $β$ are equally effective in retrieving phases but have no input-output counterparts. The geometric construction of the difference map illuminates the distinction between its fixed points and the recovered object, as well as the mechanism whereby stagnation is avoided. When support constraints are replaced by object histogram or atomicity constraints, the difference map lends itself to crystallographic phase retrieval. Numerical experiments with synthetic data suggest that structures with hundreds of atoms can be solved.

math.NA↗