activity
20242026
collaborators
Showing quant-phShow all

7 papers · 1 filter

quant-ph2025

Efficient Strategies for Reducing Sampling Error in Quantum Krylov Subspace Diagonalization

Gwonhak Lee, Seonghoon Choi, Joonsuk Huh +1

Within the realm of early fault-tolerant quantum computing (EFTQC), quantum Krylov subspace diagonalization (QKSD) has emerged as a promising quantum algorithm for the approximate…

quant-ph2025

Quantum computer formulation of the FKP-operator eigenvalue problem for probabilistic learning on manifolds

Christian Soize, Loïc Joubert-Doriol, Artur F. Izmaylov

We present a quantum computing formulation to address a challenging problem in the development of probabilistic learning on manifolds (PLoM). It involves solving the spectral probl…

quant-ph2025

Global Minimization of Electronic Hamiltonian 1-Norm via Linear Programming in the Block Invariant Symmetry Shift (BLISS) Method

Smik Patel, Aritra Sankar Brahmachari, Joshua T. Cantin +2

The cost of encoding a system Hamiltonian in a digital quantum computer as a linear combination of unitaries (LCU) grows with the 1-norm of the LCU expansion. The Block Invariant S…

quant-ph2024

Simulating Vibrational Dynamics on Bosonic Quantum Devices

Shreyas Malpathak, Sangeeth Das Kallullathil, Artur F. Izmaylov

Bosonic quantum devices, which utilize harmonic oscillator modes to encode information, are emerging as a promising alternative to conventional qubit-based quantum devices, especia…

quant-ph2024

Majorana Tensor Decomposition: A unifying framework for decompositions of fermionic Hamiltonians to Linear Combination of Unitaries

Ignacio Loaiza, Aritra Sankar Brahmachari, Artur F. Izmaylov

Linear combination of unitaries (LCU) decompositions have appeared as one of the main tools for encoding operators on quantum computers, allowing efficient implementations of arbit…

quant-ph2024

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Yuri Alexeev, Maximilian Amsler, Paul Baity +124

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…