Evidence map›Paper›PMID 40796642›Full record

ArticleScientific reports2025

On the Baltimore Light RailLink into the quantum future.

Krzysztof Domino, Emery Doucet, Reece Robertson, Bartłomiej Gardas, Sebastian Deffner

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Krzysztof Domino *Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100, Gliwice, Poland. kdomino@iitis.pl.
Emery Doucet *Department of Physics, University of Maryland, Baltimore County, Baltimore, MD, 21250, USA. emery.doucet@umbc.edu.
Reece RobertsonDepartment of Physics, University of Maryland, Baltimore County, Baltimore, MD, 21250, USA.
Bartłomiej GardasInstitute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100, Gliwice, Poland.
Sebastian DeffnerDepartment of Physics, University of Maryland, Baltimore County, Baltimore, MD, 21250, USA.

Funding

John Templeton Foundation 62422Ministerstwo Nauki i Szkolnictwa Wyższego, Poland NdS-II/SP/0336/2024/01Narodowe Centrum Nauki 2020/38/E/ST3/00269
6 · The paper itself

Abstract

In the current era of noisy intermediate-scale quantum (NISQ) technology, quantum devices present new avenues for addressing complex, real-world challenges including potentially NP-hard optimization problems. Acknowledging the fact that quantum methods underperform classical solvers, the primary goal of our research is to demonstrate how to leverage quantum noise as a computational resource for optimization. This work aims to showcase how the inherent noise in NISQ devices can be leveraged to solve such real-world problems effectively. Utilizing a D-Wave quantum annealer and IonQ's gate-based NISQ computers, we generate and analyze solutions for managing train traffic under stochastic disturbances. Our case study focuses on the Baltimore Light RailLink, which embodies the characteristics of both tramway and railway networks. We explore the feasibility of using NISQ technology to model the stochastic nature of disruptions in these transportation systems. Our research marks the inaugural application of both quantum computing paradigms to tramway and railway rescheduling, highlighting the potential of quantum noise as a beneficial resource in complex optimization scenarios.

Indexed as

NISQ deviceQuantum annealingQuantum gate computingQUBO representationStochastic optimizationTramway/railway re-scheduling

Identifiers

PMID40796642
PMCPMC12343960

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.