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A common requirement of quantum simulations and algorithms is the preparation of complex states through sequences of 2-qubit gates. For a generic quantum state, the number of gates grows exponentially with the number of qubits, becoming…

Quantum Physics · Physics 2024-07-08 Matan Ben Dov , David Shnaiderov , Adi Makmal , Emanuele G. Dalla Torre

We introduce a framework for simulating hybrid oscillator-qubit quantum processors on qubit-only systems through position encoding. By encoding continuous-variable position and momentum wave functions into qubit amplitudes, our method…

Quantum Physics · Physics 2026-03-11 Xi Lu , Bojko N. Bakalov , Yuan Liu

Efficient block encoding of many-body Hamiltonians is a central requirement for quantum algorithms in scientific computing, particularly in the early fault-tolerant era. In this work, we introduce new explicit constructions for block…

Quantum Physics · Physics 2025-10-13 Diyi Liu , Shuchen Zhu , Guang Hao Low , Lin Lin , Chao Yang

Artificial intelligence (AI) provides an alternative way to design channel coding with affordable complexity. However, most existing studies can only learn codes for a given size and rate, typically defined by a fixed network architecture…

Signal Processing · Electrical Eng. & Systems 2024-11-28 Yukun Cheng , Wei Chen , Tianwei Hou , Geoffrey Ye Li , Bo Ai

We present the first version of the QEngine, an open-source C++ library for simulating and controlling ultracold quantum systems using optimal control theory (OCT). The most notable systems presented here are Bose-Einstein condensates,…

Quantum Physics · Physics 2019-07-24 Jens Jakob Sørensen , Jesper Jensen , Till Heinzel , Jacob Sherson

Quantum computation of vibrational properties of molecules is a promising platform to obtain computational advantages for computational chemistry. However, fault-tolerant quantum computations of vibrational properties remain a relatively…

Quantum machine learning is an approach that aims to improve the performance of machine learning methods by leveraging the properties of quantum computers. In quantum circuit learning (QCL), a supervised learning method that can be…

Quantum algorithm design usually assumes access to a perfect quantum computer with ideal properties like full connectivity, noise-freedom and arbitrarily long coherence time. In Noisy Intermediate-Scale Quantum (NISQ) devices, however, the…

Quantum Physics · Physics 2020-09-11 Xiangzhen Zhou , Sanjiang Li , Yuan Feng

A quantum circuit transformation (QCT) is required when executing a quantum program in a real quantum processing unit (QPU). Through inserting auxiliary SWAP gates, a QCT algorithm transforms a quantum circuit to one that satisfies the…

Quantum Physics · Physics 2022-06-03 Xiangzhen Zhou , Yuan Feng , Sanjiang Li

Despite rapid advances in quantum hardware, noise remains a central obstacle to deploying quantum algorithms on near-term devices. In particular, random coherent errors that accumulate during circuit execution constitute a dominant and…

Quantum Physics · Physics 2026-01-29 Suying Liu , Yulong Dong , Dong An , Murphy Yuezhen Niu

Quantum Phase Estimation (QPE) is a cornerstone algorithm for fault-tolerant quantum computation, especially for electronic structure calculations of chemical systems. To accommodate the diverse characteristics of quantum chemical systems,…

Quantum Physics · Physics 2025-10-03 Calvin Ku , Yu-Cheng Chen , Alice Hu , Min-Hsiu Hsieh

We present an efficient approach to simulate real-time quantum dynamics using Projected Variational Quantum Dynamics (PVQD), where the computational cost is reduced by strategically optimizing only a subset of the variational parameters at…

Quantum Physics · Physics 2026-01-06 Harshdeep Singh , Sonjoy Majumder , Sabyashachi Mishra

Quantum computers have the potential to provide exponential speedups over their classical counterparts. Quantum principles are being applied to fields such as communications, information processing, and artificial intelligence to achieve…

Quantum Physics · Physics 2024-03-21 Arijit Mondal , Keshab K. Parhi

Quantum Fourier transform (QFT) is a widely used building block for quantum algorithms, whose scalable implementation is challenging in experiments. Here, we propose a protocol of quadratic quantum Fourier transform (QQFT), considering cold…

Quantum Physics · Physics 2022-11-02 Pei Wang , Zhijuan Huang , Xingze Qiu , Xiaopeng Li

The advent of quantum computing necessitates the transition of worldwide cryptosystems to post-quantum cryptography (PQC), which is founded upon the problem of finding short vectors in high-dimensional structured lattices. It is assumed…

Quantum Physics · Physics 2026-01-13 Eden Schirman , Cong Ling , Florian Mintert

Quantum computing is an emerging technology that has the potential to achieve exponential speedups over their classical counterparts. To achieve quantum advantage, quantum principles are being applied to fields such as communications,…

Quantum Physics · Physics 2024-04-19 Arijit Mondal , Keshab K. Parhi

We present a simplified exposition of some pieces of [Gily\'en, Su, Low, and Wiebe, STOC'19, arXiv:1806.01838], which introduced a quantum singular value transformation (QSVT) framework for applying polynomial functions to block-encoded…

Quantum Physics · Physics 2023-10-31 Ewin Tang , Kevin Tian

Hamiltonian simulation is one of the most important problems in quantum computation, and quantum singular value transformation (QSVT) is an efficient way to simulate a general class of Hamiltonians. However, the QSVT circuit typically…

Quantum Physics · Physics 2023-05-15 Yulong Dong , K. Birgitta Whaley , Lin Lin

Quantum data encoding (QDE) enables faster com-putations than classical algorithms through superposition and en-tanglement. Circuit cutting and knitting are effective techniques for ameliorating current noisy quantum processing unit (QPUs)…

Quantum Physics · Physics 2025-11-19 Ziqing Guo , Jan Balewski , Kewen Xiao , Ziwen Pan

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…

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