activity
20222026
most citedHardware-efficient learning of quantum many-body states

10 citations · 17 across the 4 of their papers we have counts for

collaborators

5 papers

quant-ph2026

Streaming Regev's Quantum Factoring Algorithm

Katherine Van Kirk, Craig Gidney

A major practical obstacle to Regev's factoring algorithm is its large space usage. In particular, the algorithm was believed to be incompatible with "qubit recycling," which strea…

quant-ph2025★ 1 cited

Parallel Spooky Pebbling Makes Regev Factoring More Practical

Gregory D. Kahanamoku-Meyer, Seyoon Ragavan, Katherine Van Kirk

Pebble games, an abstraction from classical reversible computing, have found use in the design of quantum circuits for inherently sequential tasks. Gidney showed that allowing Hada…

quant-ph2024★ 2 cited

The Jacobi Factoring Circuit: Quantum Factoring with Near-Linear Gates and Sublinear Space and Depth

Gregory D. Kahanamoku-Meyer, Seyoon Ragavan, Vinod Vaikuntanathan +1

We present a compact quantum circuit for factoring a large class of integers, including some whose classical hardness is expected to be equivalent to RSA (but not including RSA int…

quant-ph2024★ 4 cited

Learning topological states from randomized measurements using variational tensor network tomography

Yanting Teng, Rhine Samajdar, Katherine Van Kirk +5

Learning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors. While various tomographic meth…

quant-ph2022★ 10 cited

Hardware-efficient learning of quantum many-body states

Katherine Van Kirk, Jordan Cotler, Hsin-Yuan Huang +1

Efficient characterization of highly entangled multi-particle systems is an outstanding challenge in quantum science. Recent developments have shown that a modest number of randomi…