A new compilation framework treats quantum channels as first-class objects via ChannelIR and LindFront, achieving up to 99% gate count reduction on Lindbladian benchmarks versus unoptimized and Stinespring baselines.
hub Canonical reference
Simulating physics with computers
Canonical reference. 78% of citing Pith papers cite this work as background.
18
Pith papers citing it
5,621
external citations · Crossref
Background
78% of classified citations
hub tools
citation-role summary
background 9
citation-polarity summary
roles
background 9representative citing papers
Quokka# is a Python library that converts quantum circuit analysis tasks into #SAT problems, offering multiple encodings, approximate equivalence checking, and depth-optimal synthesis.
Mid-circuit stabilizer verification in six-qubit GSE-encoded Clifford Trotter steps reduces logical error rates by up to 54% on Barium ion hardware, with the gain vanishing if checks are deferred to circuit end.
SimpleTES scales test-time evaluation in LLMs to discover state-of-the-art solutions on 21 scientific problems across six domains, outperforming frontier models and optimization pipelines with examples like 2x faster LASSO and new Erdos constructions.
A circuit framework fractionalizes dyadic-order unitary operators via ancilla QFT and phase modulation, yielding explicit constructions for the quantum fractional Hartley transform and cosine-transform families of Types I and IV.
Sunlight produces polarization-entangled photons through SPDC, achieving concurrence 0.905, fidelity 0.939, and Bell violation S=2.54 exceeding the classical limit.
A two-fold quantum embedding strategy combined with machine learning integrates accurate quantum-mechanical energies into free energy calculations for biomolecular complexes and analyzes requirements for quantum computers to enhance such modeling.
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.
Simulations predict that a virtually connected photonic probabilistic computer solves Erdos-Renyi graph spin-glass ground states orders of magnitude faster than digital annealing units by avoiding embedding and sparsification.
Fermion mappings combined with Z2 tapering and frozen-core approximations reduce qubit counts by up to 50%, gate counts by up to 27.5x, and Pauli strings by up to 2.75x for VQE on small molecules.
Noise in present quantum hardware prevents reliable VQE molecular energy estimation for benzene despite Hamiltonian simplifications and optimizer tweaks, requiring substantially lower noise for future utility.
Quantum walks integrated with variational circuits and CUDA-Q acceleration generate high-fidelity adaptive probability distributions for 1D financial modeling and 2D digit patterns.
A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.
A review surveying coupling mechanisms in superconducting qubit-mechanical resonator hybrids and their extension to optomechanical architectures for quantum sensing applications.
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.
A literature review synthesizing developments in quantum Wasserstein distances, their applications, and unresolved questions.
Review of proposals and experiments using coupled cavity arrays and superconducting circuits to realize many-body physics with photons, including Mott transitions, fractional quantum Hall states, and dissipative phase transitions.
citing papers explorer
-
A Compilation Framework for Quantum Simulation of Non-unitary Dynamics
A new compilation framework treats quantum channels as first-class objects via ChannelIR and LindFront, achieving up to 99% gate count reduction on Lindbladian benchmarks versus unoptimized and Stinespring baselines.
-
Quokka#: Quantum Computing with #SAT
Quokka# is a Python library that converts quantum circuit analysis tasks into #SAT problems, offering multiple encodings, approximate equivalence checking, and depth-optimal synthesis.
-
Mid-Circuit Measurements for Clifford Noise Reduction in Hamiltonian Simulations
Mid-circuit stabilizer verification in six-qubit GSE-encoded Clifford Trotter steps reduces logical error rates by up to 54% on Barium ion hardware, with the gain vanishing if checks are deferred to circuit end.
-
Evaluation-driven Scaling for Scientific Discovery
SimpleTES scales test-time evaluation in LLMs to discover state-of-the-art solutions on 21 scientific problems across six domains, outperforming frontier models and optimization pipelines with examples like 2x faster LASSO and new Erdos constructions.
-
Dyadic-Order Quantum Fractional Transforms: Circuit Constructions and Applications to Hartley and Cosine Transform Families
A circuit framework fractionalizes dyadic-order unitary operators via ancilla QFT and phase modulation, yielding explicit constructions for the quantum fractional Hartley transform and cosine-transform families of Types I and IV.
-
Generating quantum entanglement from sunlight
Sunlight produces polarization-entangled photons through SPDC, achieving concurrence 0.905, fidelity 0.939, and Bell violation S=2.54 exceeding the classical limit.
-
How to use quantum computers for biomolecular free energies
A two-fold quantum embedding strategy combined with machine learning integrates accurate quantum-mechanical energies into free energy calculations for biomolecular complexes and analyzes requirements for quantum computers to enhance such modeling.
-
Selecting optimal unrestricted Hartree-Fock trial wavefunctions for phaseless auxiliary-field quantum Monte Carlo: Accuracy and limitations in modeling three iron-sulfur clusters
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.
-
A virtually connected probabilistic computer as a solver for higher-order, densely connected, or reconfigurable combinatorial optimisation problems
Simulations predict that a virtually connected photonic probabilistic computer solves Erdos-Renyi graph spin-glass ground states orders of magnitude faster than digital annealing units by avoiding embedding and sparsification.
-
Resource Estimation for VQE on Small Molecules: Impact of Fermion Mappings and Hamiltonian Reductions
Fermion mappings combined with Z2 tapering and frozen-core approximations reduce qubit counts by up to 50%, gate counts by up to 27.5x, and Pauli strings by up to 2.75x for VQE on small molecules.
-
Limitations of Quantum Hardware for Molecular Energy Estimation Using VQE
Noise in present quantum hardware prevents reliable VQE molecular energy estimation for benzene despite Hamiltonian simplifications and optimizer tweaks, requiring substantially lower noise for future utility.
-
Quantum Walks-Based Adaptive Distribution Generation with Efficient CUDA-Q Acceleration
Quantum walks integrated with variational circuits and CUDA-Q acceleration generate high-fidelity adaptive probability distributions for 1D financial modeling and 2D digit patterns.
-
Quantum Complexity and New Directions in Nuclear Physics and High-Energy Physics Phenomenology
A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.
-
Fundamentals and Applications of Hybrid Electro- and Opto-mechanical system coupled to Superconducting Qubit: A Short Review
A review surveying coupling mechanisms in superconducting qubit-mechanical resonator hybrids and their extension to optomechanical architectures for quantum sensing applications.
-
The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.
-
Wasserstein Distances on Quantum Structures: an Overview
A literature review synthesizing developments in quantum Wasserstein distances, their applications, and unresolved questions.
-
Many-Body Physics and Quantum Simulations with Strongly Interacting Photons
Review of proposals and experiments using coupled cavity arrays and superconducting circuits to realize many-body physics with photons, including Mott transitions, fractional quantum Hall states, and dissipative phase transitions.
- Beyond Silicon: Materials, Mechanisms, and Methods for Physical Neural Computing