26 citations · 51 across the 10 of their papers we have counts for
10 papers
Faster Quantum Monte Carlo Simulation by Random Compilation
John M. Martyn, Joshua Lin, Neill C. Warrington +2
Quantum Monte Carlo (QMC) algorithms are among the most powerful classical methods for simulating quantum systems, yet their accuracy is often limited by the systematic errors in t…
Trading Imaginary Time for Randomness in Ground State Preparation
Alvan Arulandu, John M. Martyn, Isaac L. Chuang
Imaginary-time evolution (ITE) is a foundational method for ground state preparation on quantum computers. However, because ITE is non-unitary, existing implementations incur a sam…
Analytic Approach to Quantum Control Using Quantum Signal Processing
Aishwarya Majumdar, John M. Martyn, Yuan Liu +1
Realizing coherent quantum computation requires precise and robust manipulation of quantum systems through quantum control protocols. Most quantum control techniques rely on heuris…
FTCircuitBench: A Benchmark Suite for Fault-Tolerant Quantum Compilation and Architecture
Adrian Harkness, Shuwen Kan, Chenxu Liu +10
Realizing large-scale quantum advantage is expected to require quantum error correction (QEC), making the compilation and optimization of logical operations a critical area of rese…
COMPAS: A Distributed Multi-Party SWAP Test for Parallel Quantum Algorithms
Brayden Goldstein-Gelb, Kun Liu, John M. Martyn +4
The limited number of qubits per chip remains a critical bottleneck in quantum computing, motivating the use of distributed architectures that interconnect multiple quantum process…
Hybrid Oscillator-Qubit Quantum Processors: Simulating Fermions, Bosons, and Gauge Fields
Eleanor Crane, Kevin C. Smith, Teague Tomesh +9
We develop a hybrid oscillator-qubit processor framework for quantum simulation of strongly correlated fermions and bosons that avoids the boson-to-qubit mapping overhead encounter…
Parallel Quantum Signal Processing Via Polynomial Factorization
John M. Martyn, Zane M. Rossi, Kevin Z. Cheng +2
Quantum signal processing (QSP) is a methodology for constructing polynomial transformations of a linear operator encoded in a unitary. Applied to an encoding of a state , QSP e…
Halving the Cost of Quantum Algorithms with Randomization
John M. Martyn, Patrick Rall
Quantum signal processing (QSP) provides a systematic framework for implementing a polynomial transformation of a linear operator, and unifies nearly all known quantum algorithms.…
Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform
Yuan Liu, John M. Martyn, Jasmine Sinanan-Singh +3
Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum in…
Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications
Yuan Liu, Shraddha Singh, Kevin C. Smith +11
Quantum computing with discrete variable (DV, qubit) hardware is approaching the large scales necessary for computations beyond the reach of classical computers. However, important…