Introduces the eigenwalk problem and proves a linear-diameter support-localization theorem for sparse eigenvectors, yielding poly(n)-time classical exact diagonalization for O(1)-sparse extremal eigenvectors of poly(n)-sparse 2^n-dimensional Hamiltonians.
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Quantum- centric algorithm for sample-based Krylov diagonaliza- tion
26 Pith papers cite this work. Polarity classification is still indexing.
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Real-time Krylov subspace methods are extended to Lindblad open quantum systems and demonstrated on a Kerr resonator for estimating the Liouvillian gap in cat qubit regimes.
CSQD improves SQD energy estimates in strongly correlated systems by replacing a global reference occupancy vector with cluster-specific ones, lowering energies by up to 15.95 mHa for stretched N2 and 57.82 mHa for [2Fe-2S].
HI-NQS uses a dual-channel autoregressive Transformer NQS inside an iterative sample-diagonalize-update loop to reach chemical accuracy on small molecules and nitrogen active spaces with better determinant scaling than CIPSI.
SKQD with ZZ deformation Δ=2, bitstring compression, and multiple Krylov subspaces yields relative ground-state energy errors below 0.01% on 12-site Kagome and sub-percent up to 24 sites across three geometries, extending to 72 sites with 19-36% errors.
Filter-assisted SQD uses a quantum filter to engineer sparser ground-state wavefunctions, yielding orders-of-magnitude lower energy errors and reduced sampling overhead versus standard SQD on the transverse-longitudinal Ising model.
Bowtie VarQTE is a hybrid classical-quantum variational time evolution method that exploits causal light-cones to reduce quantum resource use for state preparation while achieving fidelities comparable to approximate quantum compilation.
Fourier-based LCU decomposes diagonal and non-diagonal unitaries into hardware-friendly forms for QAOA-style optimization, trading circuit depth for sampling overhead with performance guarantees.
A tailored quantum multi-programming workflow for the LUCJ ansatz enables parallel circuit execution with SQD/ext-SQD post-processing that mitigates cross-talk, yielding ethanol energies within 0.001 kcal/mol of classical HCI references.
SQD-AA reduces total query complexity by more than 100x on model distributions and achieves the lowest T-gate counts with 3-4 orders shallower circuits than iQPE for molecular examples.
A QM/MM FEP workflow on quantum hardware with LUCJ-SQD yields binding free energies for thermolysin inhibitors in reasonable agreement with experiment and closer than classical HCI, with comparable run times.
A Transformer policy optimizes quantum circuit ansatzes for QSCI, yielding up to 98% reduction in two-qubit gates while reaching chemical accuracy on N2 and competitive compactness with classical methods.
QFTLM computes thermal expectation values on quantum computers by merging quantum Krylov methods with efficient typical-state preparation for trace estimation.
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
Quantum computed moments method on IBM hardware estimates water dipole moment to 0.03 debye of FCI, outperforming VQE by factor of two in error.
A QSCI variant using stochastic quantum time evolution selects compact configuration subspaces for SiH4 energies, achieving over 200x reduction versus conventional SCI at large separations while matching Heatbath CI compactness.
I-QMapper is a Jupyter-based interactive tool that combines qubit layout construction with real-time and historical calibration analytics for error-aware mapping on superconducting NISQ devices.
QPatLib v1.0 releases benchmark measurement patterns for measurement-based quantum simulation of Pauli-string unitaries, with scalable conventions for commuting subsets.
Chemical properties and symmetries, not variational energy, should guide UHF trial selection for ph-AFQMC on iron-sulfur clusters, yielding accurate energies despite suboptimal sampling and bias compensation.
ffsim is a new open-source library that accelerates fermionic quantum circuit simulation by using particle number and spin symmetries to cut memory and runtime, outperforming FQE on benchmarks up to 64 qubits.
SQD needs an exponentially increasing number of computational-basis configurations to approximate ground-state energies of Heisenberg and Hubbard models within fixed accuracy, even when configurations are chosen optimally by probability.
Geometric frustration in a square-lattice Ising model with diagonal couplings produces strongly inhomogeneous correlations that standard Hamiltonian-inspired variational ansatze cannot capture efficiently, increasing required circuit depth until bond-resolved parameters are introduced.
Introduces ghost Gutzwiller quantum embedding for ground-state and spectral simulations of correlated electrons on quantum devices, tested on the infinite-dimensional Hubbard model with error mitigation.
Symmetry and frustration in power-of-p and Fibonacci graphs drive distinct ground-state phase behaviors in sparse long-range quantum models, unified by an effective-geometry principle.
citing papers explorer
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Polynomial-time exact diagonalization via sparse guided eigenwalks
Introduces the eigenwalk problem and proves a linear-diameter support-localization theorem for sparse eigenvectors, yielding poly(n)-time classical exact diagonalization for O(1)-sparse extremal eigenvectors of poly(n)-sparse 2^n-dimensional Hamiltonians.
-
Real-time Krylov Diagonalisation for Open Quantum Systems
Real-time Krylov subspace methods are extended to Lindblad open quantum systems and demonstrated on a Kerr resonator for estimating the Liouvillian gap in cat qubit regimes.
-
Cluster-Adaptive Sample-Based Quantum Diagonalization for Strongly Correlated Systems
CSQD improves SQD energy estimates in strongly correlated systems by replacing a global reference occupancy vector with cluster-specific ones, lowering energies by up to 15.95 mHa for stretched N2 and 57.82 mHa for [2Fe-2S].
-
Ground-state estimation of the Heisenberg model on frustrated lattices with Sample-based Krylov Quantum Diagonalization
SKQD with ZZ deformation Δ=2, bitstring compression, and multiple Krylov subspaces yields relative ground-state energy errors below 0.01% on 12-site Kagome and sub-percent up to 24 sites across three geometries, extending to 72 sites with 19-36% errors.
-
Filter-assisted quantum subspace diagonalization via wavefunction sparsity engineering
Filter-assisted SQD uses a quantum filter to engineer sparser ground-state wavefunctions, yielding orders-of-magnitude lower energy errors and reduced sampling overhead versus standard SQD on the transverse-longitudinal Ising model.
-
Bowtie VarQTE: A Resource-Efficient Quantum State Preparation Primitive
Bowtie VarQTE is a hybrid classical-quantum variational time evolution method that exploits causal light-cones to reduce quantum resource use for state preparation while achieving fidelities comparable to approximate quantum compilation.
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Efficient Fourier-Based Linear Combination of Unitaries and Applications in Quantum Optimization
Fourier-based LCU decomposes diagonal and non-diagonal unitaries into hardware-friendly forms for QAOA-style optimization, trading circuit depth for sampling overhead with performance guarantees.
-
A Quantum Multi-Programming Framework to Maximize Quantum Resources for the LUCJ Ansatz
A tailored quantum multi-programming workflow for the LUCJ ansatz enables parallel circuit execution with SQD/ext-SQD post-processing that mitigates cross-talk, yielding ethanol energies within 0.001 kcal/mol of classical HCI references.
-
Sample-Based Quantum Diagonalization with Amplitude Amplification
SQD-AA reduces total query complexity by more than 100x on model distributions and achieves the lowest T-gate counts with 3-4 orders shallower circuits than iQPE for molecular examples.
-
Protein-Ligand Free Energy Perturbation on Quantum Hardware
A QM/MM FEP workflow on quantum hardware with LUCJ-SQD yields binding free energies for thermolysin inhibitors in reasonable agreement with experiment and closer than classical HCI, with comparable run times.
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Generative Circuit Design for Quantum-Selected Configuration Interaction
A Transformer policy optimizes quantum circuit ansatzes for QSCI, yielding up to 98% reduction in two-qubit gates while reaching chemical accuracy on N2 and competitive compactness with classical methods.
-
Quantum Finite Temperature Lanczos Method
QFTLM computes thermal expectation values on quantum computers by merging quantum Krylov methods with efficient typical-state preparation for trace estimation.
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Benchmarking quantum simulation with neutron-scattering experiments
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
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Moments-based quantum computation of the electric dipole moment of molecular systems
Quantum computed moments method on IBM hardware estimates water dipole moment to 0.03 debye of FCI, outperforming VQE by factor of two in error.
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Towards Compact Wavefunctions from Quantum-Selected Configuration Interaction
A QSCI variant using stochastic quantum time evolution selects compact configuration subspaces for SiH4 energies, achieving over 200x reduction versus conventional SCI at large separations while matching Heatbath CI compactness.
-
I-QMapper: Error-Aware Layout Optimization and Device Diagnostics for NISQ Hardware
I-QMapper is a Jupyter-based interactive tool that combines qubit layout construction with real-time and historical calibration analytics for error-aware mapping on superconducting NISQ devices.
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Scalable Measurement-Based Quantum Simulation Patterns for Benchmarking
QPatLib v1.0 releases benchmark measurement patterns for measurement-based quantum simulation of Pauli-string unitaries, with scalable conventions for commuting subsets.
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ffsim: Faster simulation of fermionic quantum circuits
ffsim is a new open-source library that accelerates fermionic quantum circuit simulation by using particle number and spin symmetries to cut memory and runtime, outperforming FQE on benchmarks up to 64 qubits.
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A Critical Assessment of the Sample-Based Quantum Diagonalization for Heisenberg and Hubbard Models
SQD needs an exponentially increasing number of computational-basis configurations to approximate ground-state energies of Heisenberg and Hubbard models within fixed accuracy, even when configurations are chosen optimally by probability.
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Frustration-Induced Expressibility Limitations in Variational Quantum Algorithms
Geometric frustration in a square-lattice Ising model with diagonal couplings produces strongly inhomogeneous correlations that standard Hamiltonian-inspired variational ansatze cannot capture efficiently, increasing required circuit depth until bond-resolved parameters are introduced.
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Quantum-Classical Embedding via Ghost Gutzwiller Approximation for Enhanced Simulations of Correlated Electron Systems
Introduces ghost Gutzwiller quantum embedding for ground-state and spectral simulations of correlated electrons on quantum devices, tested on the infinite-dimensional Hubbard model with error mitigation.
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Interaction geometry and ground-state properties of sparse quantum lattice models
Symmetry and frustration in power-of-p and Fibonacci graphs drive distinct ground-state phase behaviors in sparse long-range quantum models, unified by an effective-geometry principle.
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Additive binding energies in asphalt on a quantum processor via quantum-selected configuration interaction (QSCI)
Hybrid quantum workflow on IQM Emerald processor computes -3.52 kcal/mol binding energy for pyridine-phenol complex via QSCI in (10e,10o) space, matching CASCI but underbinding relative to CCSD(T) benchmark of -8.5 to -9.5 kcal/mol.