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A geometrically uniform (GU) ensemble is a uniformly weighted quantum state ensemble generated from a fixed state by a unitary representation of a finite group $G$. In this work we analyze the problem of discriminating GU ensembles from…

Quantum Physics · Physics 2026-01-21 Juntai Zhou , Stefano Chessa , Eric Chitambar , Felix Leditzky

Group-testing refers to the problem of identifying (with high probability) a (small) subset of $D$ defectives from a (large) set of $N$ items via a "small" number of "pooled" tests. For ease of presentation in this work we focus on the…

Information Theory · Computer Science 2013-07-11 Sheng Cai , Mohammad Jahangoshahi , Mayank Bakshi , Sidharth Jaggi

Iteration of the modular l-th power function f(x) = x^l (mod n) provides a common pseudorandom number generator (known as the Blum-Blum-Shub generator when l=2). The period of this pseudorandom number generator is closely related to…

Number Theory · Mathematics 2015-06-26 Greg Martin , Carl Pomerance

The permutation groups of cyclic codes are widely applicable in determining the weight distribution of codes, decoding theory and various other areas. In this paper, by employing two distinct matrix representations, we can relate cyclic…

Information Theory · Computer Science 2026-05-26 Junjie Huang , Jicheng Ma , Chang-An Zhao

In this work, lossy distributed compression of pairs of correlated sources is considered. Conventionally, Shannon's random coding arguments -- using randomly generated unstructured codebooks whose blocklength is taken to be asymptotically…

Information Theory · Computer Science 2020-10-21 Farhad Shirani , S. Sandeep Pradhan

Trevisan has shown that constructions of pseudo-random generators from hard functions (the Nisan-Wigderson approach) also produce extractors. We show that constructions of pseudo-random generators from one-way permutations (the…

Computational Complexity · Computer Science 2007-05-23 Marius Zimand

We introduce a simple, accurate, and extremely efficient method for numerically solving the multi-marginal optimal transport (MMOT) problems arising in density functional theory. The method relies on (i) the sparsity of optimal plans [for…

Machine Learning · Computer Science 2021-03-24 Gero Friesecke , Andreas S. Schulz , Daniela Vögler

We develop techniques to prove lower bounds for the BCAST(log n) Broadcast Congested Clique model (a distributed message passing model where in each round, each processor can broadcast an O(log n)-sized message to all other processors). Our…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-21 Lijie Chen , Ofer Grossman

In topologically-protected quantum computation, quantum gates can be carried out by adiabatically braiding two-dimensional quasiparticles, reminiscent of entangled world lines. Bonesteel et al. [Phys. Rev. Lett. 95, 140503 (2005)], as well…

Quantum Physics · Physics 2013-02-14 Ross B. McDonald , Helmut G. Katzgraber

This paper studies a Group Influence with Minimum cost which aims to find a seed set with smallest cost that can influence all target groups, where each user is associated with a cost and a group is influenced if the total score of the…

Computer Science and Game Theory · Computer Science 2022-12-16 Phuong N. H. Pham , Canh V. Pham , Hieu V. Duong , Thanh T. Nguyen , My T. Thai

The ultimate random number generators are those certified to be unpredictable -- including to an adversary. The use of simple quantum processes promises to provide numbers that no physical observer could predict but, in practice, unwanted…

As a kind of generative self-supervised learning methods, generative adversarial nets have been widely studied in the field of anomaly detection. However, the representation learning ability of the generator is limited since it pays too…

Computer Vision and Pattern Recognition · Computer Science 2021-07-28 Xuan Xia , Xizhou Pan , Xing He , Jingfei Zhang , Ning Ding , Lin Ma

Pseudo-random number generators (PRNGs) are high-nonlinear processes, and they are key blocks in optimization of Large language models. Transformers excel at processing complex nonlinear relationships. Thus it is reasonable to generate…

Machine Learning · Computer Science 2025-08-05 Ran Li , Lingshu Zeng

This paper investigates the maximal subgroups of a free projection-generated regular $*$-semigroup $PG(P)$ over a projection algebra $P$, and their relationship to the maximal subgroups of the free idempotent-generated semigroup $IG(E)$…

Group Theory · Mathematics 2025-07-10 James East , Robert D. Gray , P. A. Azeef Muhammed , Nik Ruskuc

In a recent work, O'Donnell, Servedio and Tan (STOC 2019) gave explicit pseudorandom generators (PRGs) for arbitrary $m$-facet polytopes in $n$ variables with seed length poly-logarithmic in $m,n$, concluding a sequence of works in the last…

Computational Complexity · Computer Science 2021-06-03 Srinivasan Arunachalam , Penghui Yao

We present results of extensive bit level tests on some pseudorandom number generators which are commonly used in physics applications. The generators have first been tested with an extended version of the $d$-tuple test. Second, we have…

High Energy Physics - Lattice · Physics 2009-10-22 K. Kankaala , T. Ala-Nissila , I. Vattulainen

We introduce a novel family of expander-based error correcting codes. These codes can be sampled with randomness linear in the block-length, and achieve list-decoding capacity (among other local properties). Our expander-based codes can be…

Combinatorics · Mathematics 2023-04-11 Aaron L Putterman , Edward Pyne

In this survey we summarize properties of pseudorandomness and non-randomness of some number-theoretic sequences and present results on their behaviour under the following measures of pseudorandomness: balance, linear complexity,…

Number Theory · Mathematics 2023-05-22 Arne Winterhof

We give a pseudorandom generator that fools degree-$d$ polynomial threshold functions over $n$-dimensional Gaussian space with seed length $\mathrm{poly}(d)\cdot \log n$. All previous generators had a seed length with at least a $2^d$…

Computational Complexity · Computer Science 2022-02-10 Ryan O'Donnell , Rocco A. Servedio , Li-Yang Tan , Daniel Kane

Maximizing a submodular function has a wide range of applications in machine learning and data mining. One such application is data summarization whose goal is to select a small set of representative and diverse data items from a large…

Machine Learning · Computer Science 2023-03-10 Jing Yuan , Shaojie Tang