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We present an algorithm for measurement of $k$-local operators in a quantum state, which scales logarithmically both in the system size and the output accuracy. The key ingredients of the algorithm are a digital representation of the…

Quantum Physics · Physics 2018-10-16 Apoorva Patel , Anjani Priyadarsini

Quantum Signal Processing (QSP) and Quantum Singular Value Transformation (QSVT) provide an efficient framework for implementing polynomials of block-encoded matrices, and thus offer a systematic approach to quantum algorithm design.…

Quantum Physics · Physics 2026-04-22 Xabier Gutiérrez , Lorenzo Laneve , Mikel Sanz

This PhD thesis explores the potential of quantum computing to address computational challenges in high-energy physics (HEP). As the Standard Model (SM) leaves key questions unanswered and no signs of new physics have emerged since the…

Quantum Physics · Physics 2025-12-02 Jorge J. Martínez de Lejarza

Quantum computing opens up new possibilities for the simulation of many-body nuclear systems. As the number of particles in a many-body system increases, the size of the space if the associated Hamiltonian increases exponentially. This…

Quantum Physics · Physics 2022-09-19 Isaac Hobday , Paul Stevenson , James Benstead

Estimating the eigenvalue or energy gap of a Hamiltonian H is vital for studying quantum many-body systems. Particularly, many of the problems in quantum chemistry, condensed matter physics, and nuclear physics investigate the energy gap…

Quantum Physics · Physics 2023-05-22 Yongdan Yang , Ying Li , Xiaosi Xu , Xiao Yuan

The use of near-term quantum devices that lack quantum error correction, for addressing quantum chemistry and physics problems, requires hybrid quantum-classical algorithms and techniques. Here we present a process for obtaining the…

Quantum Physics · Physics 2023-08-14 Pejman Jouzdani , Stefan Bringuier

We investigate the possibility to calculate the ground-state energy of the atomic systems on a quantum computer. For this purpose we evaluate the lowest binding energy of the moscovium atom with the use of the iterative phase estimation and…

Quantum Physics · Physics 2023-09-26 V. A. Zaytsev , M. E. Groshev , I. A. Maltsev , A. V. Durova , V. M. Shabaev

Quantum computing can potentially provide advantages for specific computational tasks. The simulation of fermionic systems is one such task that lends itself well to quantum computation, with applications in nuclear physics and electronic…

Quantum Physics · Physics 2024-03-14 Isaac Hobday , Paul Stevenson , James Benstead

The study and prediction of chemical reactivity is one of the most important application areas of molecular quantum chemistry. Large-scale, fully error-tolerant quantum computers could provide exact or near-exact solutions to the underlying…

Quantum Physics · Physics 2019-09-12 Michael Kühn , Sebastian Zanker , Peter Deglmann , Michael Marthaler , Horst Weiß

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is: how might we use imperfect near-term quantum computers to solve problems of practical value? We…

Quantum Physics · Physics 2023-08-29 Phillip W. K. Jensen , Peter D. Johnson , Alexander A. Kunitsa

This paper proposes a very simple perturbative technique to calculate the low-lying eigenvalues and eigenstates of a parity-symmetric quantum-mechanical potential. The technique is to solve the time-independent Schroedinger eigenvalue…

Quantum Physics · Physics 2015-06-18 Carl M. Bender , Hugh F. Jones

We present an algorithm to compute Green's functions on quantum computers for interacting electron systems, which is a challenging task on conventional computers. It uses a continued fraction representation based on the Lanczos method,…

Quantum Physics · Physics 2022-12-07 Francois Jamet , Abhishek Agarwal , Ivan Rungger

Krylov subspace methods are an essential building block in numerical simulation software. The efficient utilization of modern hardware is a challenging problem in the development of these methods. In this work, we develop Krylov subspace…

Numerical Analysis · Mathematics 2021-04-07 Nils-Arne Dreier

Recent work introduced a new framework for analyzing correlation functions with improved convergence and signal-to-noise properties, as well as rigorous quantification of excited-state effects, based on the Lanczos algorithm and spurious…

High Energy Physics - Lattice · Physics 2025-08-25 Daniel C. Hackett , Michael L. Wagman

Quantum computing architectures require an accurate and efficient description in terms of many-electron states. Recent implementations include quantum dot arrays, where the ground state of a multi q-bit system can be altered by voltages…

Mesoscale and Nanoscale Physics · Physics 2022-09-27 G. A. Nemnes , T. L. Mitran , A. T. Preda , I. Ghiu , M. Marciu , A. Manolescu

A majority of numerical scientific computation relies heavily on handling and manipulating matrices, such as solving linear equations, finding eigenvalues and eigenvectors, and so on. Many quantum algorithms have been developed to advance…

Quantum Physics · Physics 2023-11-10 Nhat A. Nghiem , Tzu-Chieh Wei

The performance of quantum algorithms for ground-state energy estimation is directly impacted by the quality of the initial state, where quality is traditionally defined in terms of the overlap of the input state with the target state. An…

Measurement of the energy eigenvalues (spectrum) of a multi-qubit system has recently become possible by qubit tunneling spectroscopy (QTS). In the standard QTS experiments, an incoherent probe qubit is strongly coupled to one of the qubits…

Quantum Physics · Physics 2018-02-22 Anatoly Yu. Smirnov , Mohammad H. Amin

While quantum algorithms for simulation exhibit better asymptotic scaling than their classical counterparts, they currently cannot be implemented on real-world devices. Instead, chemists and computer scientists rely on costly classical…

Quantum Physics · Physics 2022-06-03 Christopher Kang , Nicholas P. Bauman , Sriram Krishnamoorthy , Karol Kowalski

The numerical solution of eigenvalue problems is essential in various application areas of scientific and engineering domains. In many problem classes, the practical interest is only a small subset of eigenvalues so it is unnecessary to…

Numerical Analysis · Mathematics 2023-11-16 M. Ridwan Apriansyah , Rio Yokota