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We consider a disordered d--wave superconductor in two dimensions. Recently, we have shown in an exact calculation that for a lattice model with a Lorentzian distributed random chemical potential the quasiparticle density of states at the…

Superconductivity · Physics 2009-10-30 K. Ziegler , M. H. Hettler , P. J. Hirschfeld

The Holstein Hamiltonian describes fermions hopping on a lattice and interacting locally with dispersionless phonon degrees of freedom. In the low density limit, dressed quasiparticles, polarons and bipolarons, propagate with an effective…

Strongly Correlated Electrons · Physics 2021-06-09 Owen Bradley , George G. Batrouni , Richard T. Scalettar

Lattice codes with optimal decoding coefficient are capacity-achieving when dimension $N \rightarrow \infty$. In communications systems, finite dimensional lattice codes are considered, where the optimal decoding coefficients may still fail…

Information Theory · Computer Science 2025-01-09 Jiajie Xue , Brian M. Kurkoski

In this article we revisit smoothing bounds in parallel between lattices $and$ codes. Initially introduced by Micciancio and Regev, these bounds were instantiated with Gaussian distributions and were crucial for arguing the security of many…

Information Theory · Computer Science 2022-09-09 Thomas Debris-Alazard , Léo Ducas , Nicolas Resch , Jean-Pierre Tillich

All approaches currently used to study finite baryon density lattice QCD suffer from uncontrolled systematic uncertainties in addition to the well-known sign problem. We formulate and test an algorithm, sign reweighting, that works directly…

High Energy Physics - Lattice · Physics 2020-06-24 Matteo Giordano , Kornel Kapas , Sandor D. Katz , Daniel Nogradi , Attila Pasztor

Neural network decoding algorithms are recently introduced by Nachmani et al. to decode high-density parity-check (HDPC) codes. In contrast with iterative decoding algorithms such as sum-product or min-sum algorithms in which the weight of…

Information Theory · Computer Science 2018-09-14 Mohammad-Reza Sadeghi , Farzane Amirzade , Daniel Panario , Amin Sakzad

In a recent study by Euclid collaboration, the halo mass function (HMF) has been fitted with accuracy better than $1\%$ for the $\Lambda$CDM model. Several parameters were introduced and fitted against N-body simulations, assuming the usual…

Cosmology and Nongalactic Astrophysics · Physics 2025-05-08 Ronaldo C. Batista

We consider first-passage percolation on the $d$ dimensional cubic lattice for $d \geq 2$; that is, we assign independently to each edge $e$ a nonnegative random weight $t_e$ with a common distribution and consider the induced random graph…

Probability · Mathematics 2016-04-21 Michael Damron , Naoki Kubota

This paper investigates the problem of variable-length lossy source coding allowing a positive excess distortion probability and an overflow probability of codeword lengths. Novel one-shot achievability and converse bounds of the optimal…

Information Theory · Computer Science 2018-12-17 Shota Saito , Hideki Yagi , Toshiyasu Matsushima

We study Voronoi diagrams for distance functions that add together two convex functions, each taking as its argument the difference between Cartesian coordinates of two planar points. When the functions do not grow too quickly, then the…

Computational Geometry · Computer Science 2010-05-14 Matthew Dickerson , David Eppstein , Kevin A. Wortman

The stochastic density functional theory (DFT) [Phys. Rev. Lett. 111, 106402 (2013)] is a valuable linear scaling approach to Kohn-Sham DFT that does not rely on the sparsity of the density matrix. Linear (and often sub-linear) scaling is…

Chemical Physics · Physics 2019-02-20 Ming Chen , Roi Baer , Daniel Neuhauser , Eran Rabani

The method of distributions is developed for systems that are governed by hyperbolic conservation laws with stochastic forcing. The method yields a deterministic equation for the cumulative density distribution (CDF) of a system state,…

Computational Physics · Physics 2019-09-05 Rik J. L. Rutjens , Gustaaf B. Jacobs , Daniel M. Tartakovsky

The normal distribution is used as a unified probability distribution, however, our researcher found that it is not good agreed with the real-life dynamical system's data. We collected and analyzed representative naturally occurring data…

Dynamical Systems · Mathematics 2020-11-06 Wei Ping Cheng , Zhi Hong Zhang , Pu Wang

We seek shifted lattice rules that are good for high dimensional integration over the unit cube in the setting of an unanchored weighted Sobolev space of functions with square-integrable mixed first derivatives. Many existing studies rely…

Numerical Analysis · Mathematics 2019-03-14 Yoshihito Kazashi , Frances Y. Kuo , Ian H. Sloan

In this paper, a derandomized algorithm for sampling decoding is proposed to achieve near-optimal performance in lattice decoding. By setting a probability threshold to sample candidates, the whole sampling procedure becomes deterministic,…

Information Theory · Computer Science 2016-11-17 Zheng Wang , Shuiyin Liu , Cong Ling

While it is a common knowledge that AC coefficients of Fourier-related transforms, like DCT-II of JPEG image compression, are from Laplace distribution, there was tested more general EPD (exponential power distribution) $\rho\sim…

Information Theory · Computer Science 2021-02-23 Jarek Duda

The density of a code is the fraction of the coding space covered by packing balls centered around the codewords. This paper investigates the density of codes in the complex Stiefel and Grassmann manifolds equipped with the chordal…

Information Theory · Computer Science 2017-12-29 Renaud-Alexandre Pitaval , Lu Wei , Olav Tirkkonen , Camilla Hollanti

We study a set of many-body wave-functions of Fermions that are naturally written using momentum space basis and allow for quantum superposition of Fermion occupancy, $\{n_{\bf k}\}$. This {enables} us to capture the fluctuations of the…

Strongly Correlated Electrons · Physics 2024-08-05 Ankush Chaubey , Harsh Nigam , Subhro Bhattacharjee , K. Sengupta

In this work we derive a variant of the classic Glivenko-Cantelli Theorem, which asserts uniform convergence of the empirical Cumulative Distribution Function (CDF) to the CDF of the underlying distribution. Our variant allows for tighter…

Machine Learning · Computer Science 2017-11-07 Noga Alon , Moshe Babaioff , Yannai A. Gonczarowski , Yishay Mansour , Shay Moran , Amir Yehudayoff

We study the geometry and complexity of Voronoi cells of lattices with respect to arbitrary norms. On the positive side, we show for strictly convex and smooth norms that the geometry of Voronoi cells of lattices in any dimension is similar…

Metric Geometry · Mathematics 2017-11-15 Johannes Blömer , Kathlén Kohn