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Subspace diagonalisation methods have appeared recently as promising means to access the ground state and some excited states of molecular Hamiltonians by classically diagonalising small matrices, whose elements can be efficiently obtained…

Quantum Physics · Physics 2024-03-13 Maria-Andreea Filip , David Muñoz Ramo , Nathan Fitzpatrick

The quantum-phase-estimation algorithm (QPEA) is widely used to find estimates of unknown phases. The original algorithm relied on an input state in a uniform superposition of all possible bit strings. However, it is known that other input…

Quantum Physics · Physics 2025-05-05 Joseph G. Smith , Crispin H. W. Barnes , David R. M. Arvidsson-Shukur

Quantum chemistry is envisioned as an early and disruptive application for quantum computers. Yet, closer scrutiny of the proposed algorithms shows that there are considerable difficulties along the way. Here, we propose two criteria for…

Quantum Physics · Physics 2026-04-09 Thibaud Louvet , Thomas Ayral , Xavier Waintal

The accumulation of noise in quantum computers is the dominant issue stymieing the push of quantum algorithms beyond their classical counterparts. We do not expect to be able to afford the overhead required for quantum error correction in…

We study a variant of the quantum approximate optimization algorithm [ E. Farhi, J. Goldstone, and S. Gutmann, arXiv:1411.4028] with slightly different parametrization and different objective: rather than looking for a state which…

Quantum Physics · Physics 2016-08-17 D. Wecker , M. B. Hastings , M. Troyer

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the…

Quantum machine learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure…

Chemical Physics · Physics 2021-10-29 Manas Sajjan , Shree Hari Sureshbabu , Sabre Kais

The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find the answer, mandating reconstruction of the same input state…

Quantum phase estimation is an important routine in many quantum algorithms, particularly for estimating the ground state energy in quantum chemistry simulations. This estimation involves applying powers of a unitary to the ground state,…

Quantum Physics · Physics 2026-01-26 Kaur Kristjuhan , Dominic W. Berry

The overlap of the excited states in quasiparticle random-phase approximation (QRPA) is calculated in order to simulate the overlap of the intermediate nuclear states of the double-beta decay. Our basic idea is to use the like-particle QRPA…

Nuclear Theory · Physics 2015-06-11 J. Terasaki

While Quantum phase estimation (QPE) is at the core of many quantum algorithms known to date, its physical implementation (algorithms based on quantum Fourier transform (QFT)) is highly constrained by the requirement of high-precision…

Quantum Physics · Physics 2013-06-12 Hamed Ahmadi , Chen-Fu Chiang

Here we revisit the quantum phase estimation (QPE) algorithm, and devise an iterative method to improve the precision of QPE with propagators over a variety of time spans. For a given propagator and a certain eigenstate as input, QPE with…

Quantum Physics · Physics 2024-04-09 Junxu Li

Quantum computing holds immense promise for simulating quantum systems, a critical task for advancing our understanding of complex quantum phenomena. One of the primary goals in this domain is to accurately approximate the ground state of…

Quantum Physics · Physics 2024-11-28 Thilo R. Müller , Manuel Geiger , Christian B. Mendl

We propose an analysis of the Quantum Phase Estimation (QPE) algorithm applied to many-electron systems by investigating its free parameters such as the time step, number of phase qubits, initial state preparation, number of measurement…

Quantum Physics · Physics 2026-04-21 Wassil Sennane , Jérémie Messud

Beyond ground state energy estimation, quantum phase estimation (QPE) applied to many-electron systems has the potential to output an approximation of the ground state, enabling in a second step an evaluation of observables other than the…

Quantum Physics · Physics 2026-04-28 Jérémie Messud , Wassil Sennane

One promising field of quantum computation is the simulation of quantum systems, and specifically, the task of ground state energy estimation (GSEE). Ground state preparation (GSP) is a crucial component in GSEE algorithms, and classical…

Quantum Physics · Physics 2024-01-11 Katerina Gratsea , Jakob S. Kottmann , Peter D. Johnson , Alexander A. Kunitsa

Quantum purity amplification (QPA) is the task of coherently transforming $n$ copies of a mixed state into high-fidelity copies of a chosen eigenstate. We solve QPA in the general setting of $n$ input copies, $m$ output copies, arbitrary…

Quantum Physics · Physics 2026-05-22 Zhaoyi Li , Elias Theil , Aram W. Harrow , Isaac Chuang

We develop a phase estimation method with a distinct feature: its maximal runtime (which determines the circuit depth) is $\delta/\epsilon$, where $\epsilon$ is the target precision, and the preconstant $\delta$ can be arbitrarily close to…

Quantum Physics · Physics 2024-03-12 Zhiyan Ding , Lin Lin

We numerically investigate quantum circuit elementary-gate level instantiations of the standard Quantum Phase Estimation (QPE) algorithm for the task of computing the ground-state energy of a quantum magnet; the disordered fully-connected…

Quantum Physics · Physics 2026-03-02 Elijah Pelofske , Stephan Eidenbenz

Quantum algorithms designed for realistic quantum many-body systems, such as chemistry and materials, usually require a large number of measurements of the Hamiltonian. Exploiting different ideas, such as {importance sampling,} observable…

Quantum Physics · Physics 2023-01-18 Bujiao Wu , Jinzhao Sun , Qi Huang , Xiao Yuan
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