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.
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Quantum algorithm block-encodes Riccati solutions for m-particle m-hole RPA using Riesz projectors and QSVT, claiming linear system-size scaling under sparsity and polynomial cost in excitation rank m.
KOVAL-Q uses SAT solving to optimize and verify surface-code logical operations with general encodings, finding d-cycle CNOTs and 2d-cycle rotations that reduce FTQC application runtime by about 10 percent.
A compression protocol for controlled time evolution of local translationally invariant Hamiltonians achieves O(t polylog(t N/ε)) circuit depth with additive control overhead, demonstrated via 414 CNOT gates for iterative phase estimation on a 6×6 triangular lattice and sub-1% energy errors on a 4×4
Cobble is a domain-specific language for quantum block encodings that compiles high-level matrix expressions to optimized circuits using analyses and quantum singular value transformation, achieving 2.6x-25.4x speedups over unoptimized baselines on benchmarks.
Lattice-surgery scheduling is mapped to 3D path embedding and solved with look-ahead Dijkstra projection, yielding 3.8x lower execution time on quantum phase estimation benchmarks versus greedy scheduling.
ROQAM formulates Green's function estimation via orthogonal polynomials to preserve Hessenberg structure under finite precision, enabling lower precision with depth and outperforming QSVD by orders of magnitude in resource estimates for a quantum impurity model.
Encodes M by N matrix into quantum state using Θ(log(MN)) qubits in O(log²(MN)) time via segment tree embedded in bucket brigade QRAM with constant ancillas and O(MN) memory cells.
Precomputes rotation angles classically and adds a magnitude-then-phase procedure to enable complex-valued state preparation on BBQRAM at unchanged O(log²(MN)) query cost with no reversible arithmetic on the QPU.
citing papers explorer
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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.
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Quantum Solvers for Nonlinear Matrix Equations in Quantum Chemistry
Quantum algorithm block-encodes Riccati solutions for m-particle m-hole RPA using Riesz projectors and QSVT, claiming linear system-size scaling under sparsity and polynomial cost in excitation rank m.
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Design automation and space-time reduction for surface-code logical operations using a SAT-based EDA kernel compatible with general encodings
KOVAL-Q uses SAT solving to optimize and verify surface-code logical operations with general encodings, finding d-cycle CNOTs and 2d-cycle rotations that reduce FTQC application runtime by about 10 percent.
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Phase Estimation with Compressed Controlled Time Evolution
A compression protocol for controlled time evolution of local translationally invariant Hamiltonians achieves O(t polylog(t N/ε)) circuit depth with additive control overhead, demonstrated via 414 CNOT gates for iterative phase estimation on a 6×6 triangular lattice and sub-1% energy errors on a 4×4
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Cobble: Compiling Block Encodings for Quantum Computational Linear Algebra
Cobble is a domain-specific language for quantum block encodings that compiles high-level matrix expressions to optimized circuits using analyses and quantum singular value transformation, achieving 2.6x-25.4x speedups over unoptimized baselines on benchmarks.
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Efficient and high-performance routing of lattice-surgery paths on three-dimensional lattice
Lattice-surgery scheduling is mapped to 3D path embedding and solved with look-ahead Dijkstra projection, yielding 3.8x lower execution time on quantum phase estimation benchmarks versus greedy scheduling.
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Estimating Green's functions with a robust quantum Arnoldi method
ROQAM formulates Green's function estimation via orthogonal polynomials to preserve Hessenberg structure under finite precision, enabling lower precision with depth and outperforming QSVD by orders of magnitude in resource estimates for a quantum impurity model.
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Efficient Quantum State Preparation with Bucket Brigade QRAM
Encodes M by N matrix into quantum state using Θ(log(MN)) qubits in O(log²(MN)) time via segment tree embedded in bucket brigade QRAM with constant ancillas and O(MN) memory cells.
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Efficient Complex-Valued State Preparation on Bucket Brigade QRAM
Precomputes rotation angles classically and adds a magnitude-then-phase procedure to enable complex-valued state preparation on BBQRAM at unchanged O(log²(MN)) query cost with no reversible arithmetic on the QPU.