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While quantum circuits built from two-particle dual-unitary (maximally entangled) operators serve as minimal models of typically nonintegrable many-body systems, the construction and characterization of dual-unitary operators themselves are…

Quantum Physics · Physics 2023-01-20 Suhail Ahmad Rather , S. Aravinda , Arul Lakshminarayan

We study a scheme to implement an asymptotic unitary 3-design. The scheme implements a random Pauli once followed by the implementation of a random transvection Clifford by using state twirling. Thus the scheme is implemented in the form of…

Quantum Physics · Physics 2022-06-22 Tanmay Singal , Min-Hsiu Hsieh

A decision diagram (DD) is a graph-like data structure for homomorphic compression of Boolean and pseudo-Boolean functions. Over the past decades, decision diagrams have been successfully applied to verification, linear algebra, stochastic…

Quantum Physics · Physics 2026-02-23 Arend-Jan Quist , Tim Coopmans , Alfons Laarman

This thesis discusses the young fields of quantum pseudo-randomness and quantum learning algorithms. We present techniques for derandomising algorithms to decrease randomness resource requirements and improve efficiency. One key object in…

Quantum Physics · Physics 2010-06-29 Richard A. Low

A spherical $t$-design is a finite subset $X$ of the unit sphere such that every polynomial of degree at most $t$ has the same average over $X$ as it does over the entire sphere. Determining the minimum possible size of spherical designs,…

Statistics Theory · Mathematics 2026-01-13 Travis Dillon

With the dramatic growth in the number of application domains that generate probabilistic, noisy and uncertain data, there has been an increasing interest in designing algorithms for geometric or combinatorial optimization problems over…

Data Structures and Algorithms · Computer Science 2016-05-24 Lingxiao Huang , Jian Li , Jeff M. Phillips , Haitao Wang

This paper addresses the problem of designing universal quantum circuits to transform $k$ uses of a $d$-dimensional unitary input-operation into a unitary output-operation in a probabilistic heralded manner. Three classes of protocols are…

Quantum Physics · Physics 2020-04-16 Marco Túlio Quintino , Qingxiuxiong Dong , Atsushi Shimbo , Akihito Soeda , Mio Murao

Resource-efficient and high-precision approximate synthesis of quantum circuits expressed in the Clifford+T gate set is vital for Fault-Tolerant quantum computing. Efficient optimal methods are known for single-qubit RZ unitaries, otherwise…

Quantum Physics · Physics 2026-04-27 Mathias Weiden , Justin Kalloor , John Kubiatowicz , Ed Younis , Costin Iancu

We show that a tessellation generated by a small number of random affine hyperplanes can be used to approximate Euclidean distances between any two points in an arbitrary bounded set $T$, where the random hyperplanes are generated by…

Information Theory · Computer Science 2018-08-14 Sjoerd Dirksen , Shahar Mendelson

According to a well known theorem of Haussler and Welzl (1987), any range space of bounded VC-dimension admits an $\eps$-net of size $O\left(\frac{1}{\eps}\log\frac1{\eps}\right)$. Using probabilistic techniques, Pach and Woeginger (1990)…

Discrete Mathematics · Computer Science 2010-12-07 János Pach , Gábor Tardos

The famous Johnson-Lindenstrauss lemma states that for any set of n vectors, there is a linear transformation into a space of dimension O(log n) that approximately preserves all their lengths. In fact, a Haar random unitary transformation…

Quantum Physics · Physics 2018-07-25 Pranab Sen

While implementing a quantum algorithm it is crucial to reduce the quantum resources, in order to obtain the desired computational advantage. For most fault-tolerant quantum error-correcting codes the cost of implementing the non-Clifford…

Quantum Physics · Physics 2023-02-10 Vlad Gheorghiu , Michele Mosca , Priyanka Mukhopadhyay

Efficient measures to determine similarity of quantum states, such as the fidelity metric, have been widely studied. In this paper, we address the problem of defining a similarity measure for quantum operations that can be…

Quantum Physics · Physics 2022-11-23 Yiyou Chen , Hideyuki Miyahara , Louis-S. Bouchard , Vwani Roychowdhury

The efficiency of locally generating unitary designs, which capture statistical notions of quantum pseudorandomness, lies at the heart of wide-ranging areas in physics and quantum information technologies. While there are extensive potent…

Quantum Physics · Physics 2024-12-30 Zimu Li , Han Zheng , Zi-Wen Liu

We show that a quantum channel $\mathcal{N}$ constructed by averaging over $\mathcal{O}(\log d/\epsilon^2)$ randomly chosen unitaries gives a local $\epsilon$-randomizing map with non-negative probability. The idea comes from a small…

Quantum Physics · Physics 2010-02-19 Dong Pyo Chi , Kabgyun Jeong

In this work we give an efficient construction of unitary $k$-designs using $\tilde{O}(k\cdot poly(n))$ quantum gates, as well as an efficient construction of a parallel-secure pseudorandom unitary (PRU). Both results are obtained by giving…

We study the problem of constructing strong approximate unitary $k$-designs on $D$-dimensional grids (and more generally on Cartesian products of graphs), building on the work of Schuster et al. arXiv:2509.26310 which establishes strong…

Quantum Physics · Physics 2026-05-06 Marten Folkertsma , Lorenzo Grevink , Jonas Helsen , Alicja Dutkiewicz

Pseudorandom circuits generate quantum states and unitary operators which are approximately distributed according to the unitarily invariant Haar measure. We explore how several design parameters affect the efficiency of pseudo-random…

Quantum Physics · Physics 2009-11-13 Yaakov S. Weinstein , Winton G. Brown , Lorenza Viola

VC-dimension and $\varepsilon$-nets are key concepts in Statistical Learning Theory. Intuitively, VC-dimension is a measure of the size of a class of sets. The famous $\varepsilon$-net theorem, a fundamental result in Discrete Geometry,…

Machine Learning · Computer Science 2024-10-10 Sujoy Bhore , Devdan Dey , Satyam Singh

We present memory-efficient deterministic algorithms for constructing epsilon-nets and epsilon-approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their…

Computational Geometry · Computer Science 2007-06-14 Amitabha Bagchi , Amitabh Chaudhary , David Eppstein , Michael T. Goodrich