Development of superfluid helium-3 bolometry using nanowire resonators with SQUID readout for the QUEST-DMC experiment

(2025)

Authors:

DMC Collaboration, E Leason, LV Levitin, S Autti, E Bloomfield, A Casey, N Darvishi, N Eng, P Franchini, RP Haley, PJ Heikkinen, A Jennings, A Kemp, J March-Russell, A Mayer, J Monroe, D M脙录nstermann, MT Noble, JR Prance, X Rojas, T Salmon, J Saunders, J Smirnov, R Smith, MD Thompson, A Thomson, A Ting, V Tsepelin, SM West, L Whitehead, DE Zmeev

A Prediction for Maximum Supercooling in SU(N) Confinement Transition

(2025)

Authors:

Prateek Agrawal, Gaurang Ramakant Kane, Vazha Loladze, John March-Russell

Multi-Energy and Multi-Sample Searches for Neutrinos from GW Events

ArXiv 2508.09034 (2025)

Authors:

Balagopal V Aswathi, Sam Hori, Justin Vandenbroucke

Investigation of Electromagnetic and Muonic Air-Shower Components using IceTop Simulations

ArXiv 2508.08478 (2025)

Authors:

Lincoln Draper, Fahim Varsi, Dennis Soldin

Enhancing the energy gap of random graph problems via XX-catalysts in quantum annealing

Quantum Science and Technology IOP Publishing 10:4 (2025) 045010

Authors:

Luca A Nutricati, Roopayan Ghosh, Natasha Feinstein, Sougato Bose, PA Warburton

Abstract:

One of the main challenges in solving combinatorial optimisation problems with quantum annealers is the emergence of extremely small energy gaps between the ground state and the first excited state of the annealing Hamiltonian. These small gaps may be symptoms of an underlying first-order phase transition, which, according to the adiabatic theorem, can significantly extend the required anneal time, making practical implementation effectively infeasible. In this paper we demonstrate that attaching an XX-catalyst on all the edges of a graph upon which a MWIS (Maximum Weighted Independent Set) problem is defined, significantly enhances the minimum energy gap. Remarkably, our analysis shows that the smaller the energy gap, the more effective the catalyst is in opening it. This result is based on a detailed statistical analysis performed on a large number of randomly generated MWIS problem instances on both Erd玫s鈥揜茅nyi and Barab谩asi鈥揂lbert graphs. We perform the analysis using both stoquastic and non-stoquastic catalysts.