Quantum machine learning for chemistry and physics
Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …
pertinent patterns within a given data set with the objective of subsequent generation of …
Fermionic reduced density low-rank matrix completion, noise filtering, and measurement reduction in quantum simulations
Fermionic reduced density matrices summarize the key observables in Fermionic systems.
In electronic systems, the two-particle reduced density matrix (2-RDM) is sufficient to …
In electronic systems, the two-particle reduced density matrix (2-RDM) is sufficient to …
Entropy corrected geometric Brownian motion
The geometric Brownian motion (GBM) is widely used for modeling stochastic processes,
particularly in finance. However, its solutions are constrained by the assumption that the …
particularly in finance. However, its solutions are constrained by the assumption that the …
Time resolved quantum tomography in molecular spectroscopy by the maximal entropy approach
Attosecond science offers unprecedented precision in probing the initial moments of
chemical reactions, revealing the dynamics of molecular electrons that shape reaction …
chemical reactions, revealing the dynamics of molecular electrons that shape reaction …
Simulating noisy quantum channels via quantum state preparation algorithms
Abstract In **n et al (2017 Phys. Rev. A 96 062303) and Wei et al (2018 Sci. China Phys.
Mech. Astron. 61 70311), the authors reported an algorithm to simulate, in a circuit-based …
Mech. Astron. 61 70311), the authors reported an algorithm to simulate, in a circuit-based …
Enhanced shadow tomography of molecular excited states via the enforcement of -representability conditions by semidefinite programming
Excited-state properties of highly correlated systems are key to understanding
photosynthesis, luminescence, and the development of novel optical materials, but …
photosynthesis, luminescence, and the development of novel optical materials, but …
Hamiltonian learning from time dynamics using variational algorithms
The Hamiltonian of a quantum system governs the dynamics of the system via the
Schrodinger equation. In this paper, the Hamiltonian is reconstructed in the Pauli basis …
Schrodinger equation. In this paper, the Hamiltonian is reconstructed in the Pauli basis …
Physics-Inspired Quantum Simulation of Resonating Valence Bond States─ A Prototypical Template for a Spin-Liquid Ground State
Spin liquids─ an emergent, exotic collective phase of matter─ have garnered enormous
attention in recent years. While experimentally many prospective candidates have been …
attention in recent years. While experimentally many prospective candidates have been …
Random projection using random quantum circuits
The random sampling task performed by Google's Sycamore processor gave us a glimpse of
the “quantum supremacy era.” This has definitely shed some light on the power of random …
the “quantum supremacy era.” This has definitely shed some light on the power of random …
Quantum state tomography inspired by language modeling
L Zhong, C Guo, X Wang - arxiv preprint arxiv:2212.04940, 2022 - arxiv.org
Quantum state tomography is an elementary tool to fully characterize an unknown quantum
state. As the quantum hardware scales up in size, the standard quantum state tomography …
state. As the quantum hardware scales up in size, the standard quantum state tomography …