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Optical losses are the main obstacle to demonstrating a quantum advantage via boson sampling without leaving open the possibility of classical spoofing. We propose a method for generating low-depth optical circuits suitable for boson…

Quantum Physics · Physics 2021-10-12 R. van der Meer , S. Huber , P. W. H. Pinkse , R. García-Patrón , J. J. Renema

Noise in existing quantum processors only enables an approximation to ideal quantum computation. However, these approximations can be vastly improved by error mitigation, for the computation of expectation values, as shown by small-scale…

Accurate characterization of quantum noise, exemplified by the Pauli channel, is a cornerstone for building fault-tolerant quantum computers. A recent protocol (PRX Quantum 6, 020323 (2025)) combining channel concatenation and quantum…

Quantum Physics · Physics 2025-09-10 Yuan-Zhuo Wang , Yi-Ran Xiao , Ming-Yang Li , Shengjun Wu , Zeng-Bing Chen

Accurate and precise control of large quantum systems is paramount to achieve practical advantages on quantum devices. Therefore, benchmarking the hardware errors in quantum computers has drawn significant attention lately. Existing…

Quantum Physics · Physics 2023-01-18 Bharath Hebbe Madhusudhana

We study the estimation of the overlap between two unknown pure quantum states of a finite dimensional system, given $M$ and $N$ copies of each type. This is a fundamental primitive in quantum information processing that is commonly…

Variational algorithms are a promising paradigm for utilizing near-term quantum devices for modeling electronic states of molecular systems. However, previous bounds on the measurement time required have suggested that the application of…

A scalable Bayesian machine learning framework is introduced for estimating scalar properties of an unknown quantum state from measurement data, which bypasses full density matrix reconstruction. This work is the first to integrate the…

Quantum Physics · Physics 2025-12-08 Hyunho Cha , Wonjung Kim , Jungwoo Lee

We study the problems of quantum tomography and shadow tomography using measurements performed on individual, identical copies of an unknown $d$-dimensional state. We first revisit a known lower bound due to Haah et al. (2017) on quantum…

Quantum Physics · Physics 2025-06-12 Angus Lowe , Ashwin Nayak

The classical shadow estimation protocol is a noise-resilient and sample-efficient quantum algorithm for learning the properties of quantum systems. Its performance depends on the choice of a unitary ensemble, which must be chosen by a user…

Quantum Physics · Physics 2024-01-10 Kaifeng Bu , Dax Enshan Koh , Roy J. Garcia , Arthur Jaffe

Adaptive tomography has been widely investigated to achieve faster state tomography processing of quantum systems. Infidelity of the nearly pure states in a quantum information process generally scales as O(1/sqrt(N) ), which requires a…

Quantum Physics · Physics 2023-05-09 Hyeok Hwang , JaeKyung Choi , Eunseong Kim

We present a quantum algorithm for efficiently sampling transformed Gaussian random fields on $d$-dimensional domains, based on an enhanced version of the classical moving average method. Pointwise transformations enforcing boundedness are…

Quantum Physics · Physics 2025-08-20 Matthias Deiml , Daniel Peterseim

Fermionic ansatz state preparation is a critical subroutine in many quantum algorithms such as Variational Quantum Eigensolver for quantum chemistry and condensed matter applications. The shallowest circuit depth needed to prepare Slater…

Quantum Physics · Physics 2023-08-22 Chong Hian Chee , Daniel Leykam , Adrian M. Mak , Dimitris G. Angelakis

The Discrete Fourier Transform (DFT) is central to the analysis of uniformly sampled signals, yet many practical applications involve non-uniform sampling, requiring the Non-Uniform Discrete Fourier Transform (NUDFT). While quantum…

Quantum Physics · Physics 2026-03-18 Junaid Aftab , Yuehaw Khoo , Haizhao Yang

Near term quantum computers with a high quantity (around 50) and quality (around 0.995 fidelity for two-qubit gates) of qubits will approximately sample from certain probability distributions beyond the capabilities of known classical…

Quantum Physics · Physics 2018-01-23 Sergio Boixo , Sergei V. Isakov , Vadim N. Smelyanskiy , Hartmut Neven

Curve samplers are sampling algorithms that proceed by viewing the domain as a vector space over a finite field, and randomly picking a low-degree curve in it as the sample. Curve samplers exhibit a nice property besides the sampling…

Computational Complexity · Computer Science 2013-09-05 Zeyu Guo

It is advantageous for any quantum processor to support different classes of two-qubit quantum logic gates when compiling quantum circuits, a property that is typically not seen with existing platforms. In particular, access to a gate set…

We consider the question of learning $Q$-function in a sample efficient manner for reinforcement learning with continuous state and action spaces under a generative model. If $Q$-function is Lipschitz continuous, then the minimal sample…

Machine Learning · Computer Science 2020-06-12 Devavrat Shah , Dogyoon Song , Zhi Xu , Yuzhe Yang

We consider a version of Shor's quantum factoring algorithm such that the quantum Fourier transform is replaced by an extremely simple one where decomposition coefficients take only the values of $1,i,-1,-i$. In numerous calculations which…

Quantum Physics · Physics 2007-05-23 Felix M Lev

As a qubit is a two-level quantum system whose state space is spanned by |0>, |1>, so a qudit is a d-level quantum system whose state space is spanned by |0>,...,|d-1>. Quantum computation has stimulated much recent interest in algorithms…

Quantum Physics · Physics 2009-11-10 Stephen S. Bullock , Dianne P. O'Leary , Gavin K. Brennen

In light of recently proposed quantum algorithms that incorporate symmetries in the hope of quantum advantage, we show that with symmetries that are restrictive enough, classical algorithms can efficiently emulate their quantum counterparts…

Quantum Physics · Physics 2023-11-29 Eric R. Anschuetz , Andreas Bauer , Bobak T. Kiani , Seth Lloyd