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Under suitable assumptions, the quantum phase estimation (QPE) algorithm is able to achieve Heisenberg-limited precision scaling in estimating the ground state energy. However, QPE requires a large number of ancilla qubits and large circuit…

Quantum Physics · Physics 2022-02-04 Lin Lin , Yu Tong

The phase estimation algorithm is a powerful quantum algorithm with applications in cryptography, number theory, and simulation of quantum systems. We use this algorithm to simulate the time evolution of a system of two spin-1/2 particles…

Quantum Physics · Physics 2021-05-12 Scott Johnstun , Jean-François Van Huele

We introduce the concept of the quark quasifragmentation function (qFF) using an equal-time and spatially boosted form of the Collins-Soper fragmentation function where the out-meson fragment is replaced by the current asymptotic condition.…

High Energy Physics - Phenomenology · Physics 2024-12-30 Sebastian Grieninger , Ismail Zahed

Quantum computing promises polynomial and exponential speedups in many domains, such as unstructured search and prime number factoring. However, quantum programs yield probabilistic outputs from exponentially growing distributions and are…

Software Engineering · Computer Science 2024-10-29 Noah H. Oldfield , Christoph Laaber , Tao Yue , Shaukat Ali

By exploiting the invariance of the molecular Hamiltonian by a unitary transformation of the orbitals it is possible to significantly shorter the depth of the variational circuit in the Variational Quantum Eigensolver (VQE) algorithm by…

Quantum Physics · Physics 2025-09-03 Leonardo Ratini , Chiara Capecci , Leonardo Guidoni

Stochastic density functional theory (sDFT) is becoming a valuable tool for studying ground state properties of extended materials. The computational complexity of describing the Kohn-Sham orbitals is replaced by introducing a set of random…

Chemical Physics · Physics 2021-06-16 Ming Chen , Roi Baer , Daniel Neuhauser , Eran Rabani

In this work, we present a quantum algorithm for ground-state energy calculations of periodic solids on error-corrected quantum computers. The algorithm is based on the sparse qubitization approach in second quantization and developed for…

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

Numerical simulation of continuous variable quantum state preparation is a necessary tool for optimization of existing quantum information processing protocols. A powerful instrument for such simulation is the numerical computation in the…

Quantum Physics · Physics 2022-10-10 Jan Provazník , Radim Filip , Petr Marek

H\"uckel molecular orbital (HMO) theory provides a semi-empirical treatment of the electronic structure in conjugated {\pi}-electronic systems. A scalable system-agnostic execution of HMO theory on a quantum computer is reported here based…

Quantum Physics · Physics 2024-05-22 Harshdeep Singh , Sonjoy Majumder , Sabyashachi Mishra

Simulation of quantum chemistry is expected to be a principal application of quantum computing. In quantum simulation, a complicated Hamiltonian describing the dynamics of a quantum system is decomposed into its constituent terms, where the…

Quantum Physics · Physics 2020-03-04 Yingkai Ouyang , David R. White , Earl T. Campbell

Quantum state tomography (QST) is the gold standard technique for obtaining an estimate for the state of small quantum systems in the laboratory. Its application to systems with more than a few constituents (e.g. particles) soon becomes…

Simulating the time-evolution of quantum mechanical systems is BQP-hard and expected to be one of the foremost applications of quantum computers. We consider classical algorithms for the approximation of Hamiltonian dynamics using…

Simulating molecular systems on quantum computers requires efficient mappings from Fermionic operators to qubit operators. Traditional mappings such as Jordan-Wigner or Bravyi-Kitaev often produce high-weight Pauli terms, increasing circuit…

Quantum Physics · Physics 2025-11-13 James Brown , Tarini S Hardikar , Kenny Heitritter , Kanav Setia

Mapping spins to fermions via the Jordan-Wigner (JW) transformation can render mean-field (Hartree-Fock, HF) descriptions effective for strongly correlated spin systems. As established in recent work, the application of such approaches is…

Strongly Correlated Electrons · Physics 2026-01-21 Shadan Ghassemi Tabrizi , Thomas M. Henderson , Thomas D. Kühne , Gustavo E. Scuseria

We present a hybrid classical-quantum framework based on the Frank-Wolfe algorithm, Q-FW, for solving quadratic, linearly-constrained, binary optimization problems on quantum annealers (QA). The computational premise of quantum computers…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Alp Yurtsever , Tolga Birdal , Vladislav Golyanik

Quantum Hamiltonians that are fine-tuned to their so-called Rokhsar-Kivelson (RK) points, first presented in the context of quantum dimer models, are defined by their representations in preferred bases in which their ground state wave…

Strongly Correlated Electrons · Physics 2007-11-30 Claudio Castelnovo , Claudio Chamon , Christopher Mudry , Pierre Pujol

Quantum-selected configuration interaction (QSCI) is an approach for quantum chemical calculations using current quantum computers. In conventional QSCI, Slater determinants used for the wave function expansion are sampled by iteratively…

Quantum Physics · Physics 2025-10-03 Kenji Sugisaki , Shu Kanno , Toshinari Itoko , Rei Sakuma , Naoki Yamamoto

Quantum state tomography (QST) is a fundamental task in quantum information science that aims to reconstruct unknown quantum states from measurement data. However, the exponential growth of Hilbert-space dimension with system size makes…

Quantum Physics · Physics 2026-05-27 Zhen Qin , Michael B. Wakin , Zhihui Zhu

In this paper, we consider the general non-oblivious stochastic optimization where the underlying stochasticity may change during the optimization procedure and depends on the point at which the function is evaluated. We develop Stochastic…

Optimization and Control · Mathematics 2020-09-10 Hamed Hassani , Amin Karbasi , Aryan Mokhtari , Zebang Shen