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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

Some physical implementation schemes of quantum computing can apply two-qubit gates only on certain pairs of qubits. These connectivity constraints are commonly viewed as a significant disadvantage. For example, compiling an unrestricted…

Quantum Physics · Physics 2023-09-04 Pei Yuan , Jonathan Allcock , Shengyu Zhang

In this work, we study distributions of unitaries generated by random quantum circuits containing only symmetry-respecting gates. We develop a unified approach applicable to all symmetry groups and obtain an equation that determines the…

Quantum Physics · Physics 2024-10-16 Hanqing Liu , Austin Hulse , Iman Marvian

Recent work of Bravyi et al. and follow-up work by Bene Watts et al. demonstrates a quantum advantage for shallow circuits: constant-depth quantum circuits can perform a task which constant-depth classical (i.e., AC$^0$) circuits cannot.…

Quantum Physics · Physics 2019-11-07 Daniel Grier , Luke Schaeffer

We introduce magic-augmented Clifford circuits -- architectures in which Clifford circuits are preceded and/or followed by constant-depth circuits of non-Clifford (``magic") gates -- as a resource-efficient way to realize approximate…

Quantum Physics · Physics 2026-03-09 Yuzhen Zhang , Sagar Vijay , Yingfei Gu , Yimu Bao

We provide practical and powerful schemes for learning many properties of an unknown n-qubit quantum state using a sparing number of copies of the state. Specifically, we present a depth-modulated randomized measurement scheme that…

Unitary t-designs are distributions on the unitary group whose first t moments appear maximally random. Previous work has established several upper bounds on the depths at which certain specific random quantum circuit ensembles approximate…

Quantifying quantum states' complexity is a key problem in various subfields of science, from quantum computing to black-hole physics. We prove a prominent conjecture by Brown and Susskind about how random quantum circuits' complexity…

We present an algorithm for efficiently approximating of qubit unitaries over gate sets derived from totally definite quaternion algebras. It achieves $\varepsilon$-approximations using circuits of length $O(\log(1/\varepsilon))$, which is…

Quantum Physics · Physics 2015-10-16 Vadym Kliuchnikov , Alex Bocharov , Martin Roetteler , Jon Yard

We investigate the problem of synthesizing T-depth optimal quantum circuits over the Clifford+T gate set. First we construct a special subset of T-depth 1 unitaries, such that it is possible to express the T-depth-optimal decomposition of…

Quantum Physics · Physics 2022-09-14 Vlad Gheorghiu , Michele Mosca , Priyanka Mukhopadhyay

Random quantum circuits have played a central role in establishing the computational advantages of near-term quantum computers over their conventional counterparts. Here, we use ensembles of low-depth random circuits with local connectivity…

Quantum Physics · Physics 2021-09-29 Michael J. Gullans , Stefan Krastanov , David A. Huse , Liang Jiang , Steven T. Flammia

Pseudorandom quantum states (PRSs) and pseudorandom unitaries (PRUs) possess the dual nature of being efficiently constructible while appearing completely random to any efficient quantum algorithm. In this study, we establish fundamental…

Quantum Physics · Physics 2025-06-04 Tobias Haug , Kishor Bharti , Dax Enshan Koh

We present the first computationally-efficient algorithm for average-case learning of shallow quantum circuits with many-qubit gates. Specifically, we provide a quasi-polynomial time and sample complexity algorithm for learning unknown…

Quantum Physics · Physics 2025-06-11 Francisca Vasconcelos , Hsin-Yuan Huang

We study efficient generations of random diagonal-unitary matrices, an ensemble of unitary matrices diagonal in a given basis with randomly distributed phases for their eigenvalues. Despite the simple algebraic structure, they cannot be…

Quantum Physics · Physics 2014-01-31 Yoshifumi Nakata , Mio Murao

Random circuits giving rise to unitary designs are key tools in quantum information science and many-body physics. In this work, we investigate a class of random quantum circuits with a specific gate structure. Within this framework, we…

The task of non-local quantum computation requires implementation of a unitary on $n$ qubits between two parties with only one round of communication, ideally with minimal pre-shared entanglement. We introduce a new protocol that makes use…

Quantum Physics · Physics 2022-06-02 Kfir Dolev , Sam Cree

We present a classical algorithm that, for any $D$-dimensional geometrically-local, quantum circuit $C$ of polylogarithmic-depth, and any bit string $x \in {0,1}^n$, can compute the quantity $|<x|C|0^{\otimes n}>|^2$ to within any…

Quantum Physics · Physics 2022-02-18 Suchetan Dontha , Shi Jie Samuel Tan , Stephen Smith , Sangheon Choi , Matthew Coudron

We consider recent works on the simulation of quantum circuits using the formalism of matrix product states and the formalism of contracting tensor networks. We provide simplified direct proofs of many of these results, extending an…

Quantum Physics · Physics 2007-05-23 Richard Jozsa

Quantum pseudorandomness, also known as unitary designs, comprise a powerful resource for quantum computation and quantum engineering. While it is known in theory that pseudorandom unitary operators can be constructed efficiently, realizing…

Quantum Physics · Physics 2019-07-24 Jun Li , Zhihuang Luo , Tao Xin , Hengyan Wang , David Kribs , Dawei Lu , Bei Zeng , Raymond Laflamme

Unitary $k$-designs are distributions of unitary gates that match the Haar distribution up to its $k$-th statistical moment. They are a crucial resource for randomized quantum protocols. However, their implementation on encoded logical…

Quantum Physics · Physics 2025-08-25 Zihan Cheng , Eric Huang , Vedika Khemani , Michael J. Gullans , Matteo Ippoliti