Combines quantum-algorithm research with the development of practical quantum software, including methods for accelerating statistical estimation and extracting value from limited quantum hardware.
arXivarXivMontanaro links a theoretical question, how much faster a quantum algorithm can be, with the engineering question of what present machines can contribute. His Monte Carlo result establishes a general route to improved estimation under explicit assumptions. Later work explores quantum-generated samples as an input to classical simulation. Phasecraft provides an organizational setting for translating that research into software. The evidence supports a combination of algorithm design and company building, without treating projected advantage as an achieved commercial outcome.
PhasecraftarXivarXivThe work behind the recognition
Work, in context- 2015
Faster Monte Carlo estimation
Developed an algorithm offering a near-quadratic improvement for estimating the output of a bounded-variance randomized or quantum subroutine, with applications to partition functions.
Sole author of the Monte Carlo quantum-algorithm paper.
Source-supported recordarXiv - 2023
Quantum samples for classical simulation
With Stasja Stanisic, proposed using quantum-generated initial samples to accelerate variational Monte Carlo, studying both numerical simulations and experiments on quantum hardware.
Coauthor with Stasja Stanisic of the quantum-enhanced variational Monte Carlo proposal and study.
Source-supported recordarXiv
The evidence map
Both views link each contribution to its sources. Choose a contribution on the map or read them all in the list.
Faster Monte Carlo estimation
Quantum speedup of Monte Carlo methods
Supports: Authorship, bounded-variance assumptions and estimation speedup
Published 27 Apr 2015 · Checked 19 Sept 2026Credit & limits: Sole author of the Monte Carlo quantum-algorithm paper.
Read the full contribution| Contribution | Evidence & what it supports | Credit & limits |
|---|---|---|
| Faster Monte Carlo estimation2015 | Primary paperQuantum speedup of Monte Carlo methods Authorship, bounded-variance assumptions and estimation speedup Published 27 Apr 2015 · Checked 19 Sept 2026 | Sole author of the Monte Carlo quantum-algorithm paper. |
| Quantum samples for classical simulation2023 | Research preprintAccelerating variational quantum Monte Carlo using the variational quantum eigensolver Coauthorship and quantum-enhanced variational Monte Carlo Published 15 Jul 2023 · Checked 19 Sept 2026 | Coauthor with Stasja Stanisic of the quantum-enhanced variational Monte Carlo proposal and study. |
Follow the evidence
3 sourcesPrimary papers, institutional records and attributed announcements. Each source supports the claims linked above.
- PhasecraftInstitutional record
Phasecraft leadership
Identity, professional identification and contribution context
Checked 19 Sept 2026 - arXivPrimary paper
Quantum speedup of Monte Carlo methods
Authorship, bounded-variance assumptions and estimation speedup
Published 27 Apr 2015 · Checked 19 Sept 2026 - arXivResearch preprint
Accelerating variational quantum Monte Carlo using the variational quantum eigensolver
Coauthorship and quantum-enhanced variational Monte Carlo
Published 15 Jul 2023 · Checked 19 Sept 2026