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Molecular spin qudits based on lanthanide complexes offer a promising platform for quantum technologies, combining chemical tunability with multi-level encoding. However, experimental demonstrations of their envisaged capabilities remain…

Quantum algorithms are able to solve particular problems exponentially faster than conventional algorithms, when implemented on a quantum computer. However, all demonstrations to date have required already knowing the answer to construct…

Quantum Physics · Physics 2013-03-22 Xiao-Qi Zhou , Pruet Kalasuwan , Timothy C. Ralph , Jeremy L. O'Brien

Quantum computing is seeking to realize hardware-optimized algorithms for application-related computational tasks. NP (nondeterministic-polynomial-time) is a complexity class containing many important but intractable problems like the…

Quantum Physics · Physics 2021-08-27 Aonan Zhang , Hao Zhan , Junjie Liao , Kaimin Zheng , Tao Jiang , Minghao Mi , Penghui Yao , Lijian Zhang

Numerous quantum algorithms operate under the assumption that classical data has already been converted into quantum states, a process termed Quantum State Preparation (QSP). However, achieving precise QSP requires a circuit depth that…

Quantum Physics · Physics 2024-08-13 Yilun Zhao , Bingmeng Wang , Wenle Jiang , Xiwei Pan , Bing Li , Yinhe Han , Ying Wang

In this note we describe a simple and intriguing observation: the quantum Fourier transform (QFT) over $Z_q$, which is considered the most ``quantum'' part of Shor's algorithm, can in fact be simulated efficiently by classical computers.…

Quantum Physics · Physics 2007-05-23 Dorit Aharonov , Zeph Landau , Johann Makowsky

Quantum state preparation (QSP) is a fundamental task in quantum computing and quantum information processing. It is critical to the execution of many quantum algorithms, including those in quantum machine learning. In this paper, we…

Data Structures and Algorithms · Computer Science 2025-08-01 Xin Hong , Aochu Dai , Chenjian Li , Sanjiang Li , Shenggang Ying , Mingsheng Ying

We study quantum speedups in quantum machine learning (QML) by analyzing the quantum singular value transformation (QSVT) framework. QSVT, introduced by [GSLW, STOC'19, arXiv:1806.01838], unifies all major types of quantum speedup; in…

Quantum Physics · Physics 2024-07-30 Ainesh Bakshi , Ewin Tang

The quantum permutation algorithm provides computational speed-up over classical algorithms in determining the parity of a given cyclic permutation. For its $n$-qubit implementations, the number of required quantum gates scales…

Quantum Physics · Physics 2018-01-01 İ. Yalçınkaya , Z. Gedik

Current superconducting quantum devices impose strict connectivity constraints on quantum circuit execution, necessitating circuit transformation before executing quantum circuits on physical hardware. Numerous quantum circuit…

Quantum Physics · Physics 2024-12-24 Sanjiang Li , Xiangzhen Zhou , Yuan Feng

Rydberg atom arrays have recently emerged as one of the most promising platforms for quantum simulation and quantum information processing. However, as is the case for other experimental platforms, the longer-term success of the Rydberg…

Quantum Physics · Physics 2022-12-07 Sina Zeytinoğlu , Sho Sugiura

We introduce a method to enhance the precision and accuracy of Quantum Process Tomography (QPT) by mitigating the errors caused by state preparation and measurement (SPAM), readout and shot noise. Instead of performing QPT solely on a…

Quantum Physics · Physics 2024-02-07 Stancho G. Stanchev , Nikolay V. Vitanov

We propose a quantum classifier, which can classify data under the supervised learning scheme using a quantum feature space. The input feature vectors are encoded in a single qu$N$it (a $N$ level quantum system), as opposed to more commonly…

Quantum Physics · Physics 2020-05-12 Soumik Adhikary , Siddharth Dangwal , Debanjan Bhowmik

Due to the great difficulty in scalability, quantum computers are limited in the number of qubits during the early stages of the quantum computing regime. In addition to the required qubits for storing the corresponding eigenvector, suppose…

Quantum Physics · Physics 2013-11-15 Chen-Fu Chiang

Quantum gates are the building blocks of quantum circuits, which in turn are the cornerstones of quantum information processing. In this work, we theoretically investigate a single-step implementation of both a universal two- (CNOT) and…

Quantum Physics · Physics 2024-07-01 Luiz O. R. Solak , Daniel Z. Rossatto , Celso J. Villas-Boas

Quantum algorithms on near-term quantum processors are typically executed using shallow quantum circuits composed of one- and two-qubit gates. However, as circuit depth and gate number increase, gate imperfections and qubit decoherence…

We introduce a novel strategy, based on the use of modular variables, to encode and deterministically process quantum information using states described by continuous variables. Our formalism leads to a general recipe to adapt existing…

Quantum Physics · Physics 2014-06-26 A. Ketterer , S. P. Walborn , A. Keller , T. Coudreau , P. Milman

Characterizing quantum processes is essential for unlocking the potential of quantum devices. However, standard quantum process tomography is resource-intensive and becomes infeasible on large-scale systems. Despite alternative approaches…

Quantum Physics · Physics 2026-02-24 Hao Zhan , Zongbo Bao , Zekun Ye , Qianyi Wang , Minghao Mi , Penghui Yao , Lijian Zhang

Phase estimation algorithms are key protocols in quantum information processing. Besides applications in quantum computing, they can also be employed in metrology as they allow for fast extraction of information stored in the quantum state…

Quantum Physics · Physics 2018-07-03 S. Danilin , A. V. Lebedev , A. Vepsäläinen , G. B. Lesovik , G. Blatter , G. S. Paraoanu

We propose to implement quantum computing based on electronic spin qubits by controlling the propagation of the electron wave packets through the helical edge states of quantum spin Hall systems (QSHs). Specfically, two non-commutative…

Mesoscale and Nanoscale Physics · Physics 2014-04-04 Wei Chen , Zheng-Yuan Xue , Z. D. Wang , R. Shen , D. Y. Xing

We present an efficient tensor-network-based approach for simulating large-scale quantum circuits, demonstrated using Quantum Support Vector Machines (QSVMs). Our method effectively reduces exponential runtime growth to near-quadratic…