2026 Andrew M. Childs: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	43	7792	7568	3371	3244	113	12318

Overview

Andrew M. Childs is affiliated with the University of Maryland, College Park in the United States. Their research primarily focuses on computer science, with a significant concentration in artificial intelligence, atomic and molecular physics and optics, computational theory and mathematics, computer networks and communications, and hardware and architecture.

The main topics covered in their work include:

Quantum Computing Algorithms and Architecture
Quantum Information and Cryptography
Quantum and electron transport phenomena
Neural Networks and Reservoir Computing
Stochastic Gradient Optimization Techniques
Machine Learning and Algorithms
Quantum many-body systems

Andrew M. Childs has published extensively across several venues. Their frequent publication venues include:

arXiv (Cornell University)
Quantum
Physical Review Research
PRX Quantum
Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Some of their recent papers are:

"Efficient quantum algorithm for dissipative nonlinear differential equations," 2021, Proceedings of the National Academy of Sciences
"High-precision quantum algorithms for partial differential equations," 2021, Quantum
"Tweezer-programmable 2D quantum walks in a Hubbard-regime lattice," 2022, Science
"Signaling and scrambling with strongly long-range interactions," 2020, Physical Review A
"Quantum algorithms and lower bounds for convex optimization," 2020, Quantum

Collaboration plays a notable role in their research. Frequent co-authors include:

Alexey V. Gorshkov (21 collaborations)
Dhruv Devulapalli (11 collaborations)
Tongyang Li (10 collaborations)
Eddie Schoute (8 collaborations)
Daochen Wang (6 collaborations)

Best Publications

Universal Computation by Quantum Walk

Andrew M. Childs

1184
Citations
Exponential algorithmic speedup by a quantum walk

Andrew M. Childs;Richard Cleve;Enrico Deotto;Edward Farhi

925
Citations
Spatial search by quantum walk

Andrew M. Childs;Jeffrey Goldstone

823
Citations
Simulating Hamiltonian Dynamics with a Truncated Taylor Series

Dominic W. Berry;Andrew M. Childs;Richard Cleve;Richard Cleve;Robin Kothari;Robin Kothari

790
Citations
Robustness of adiabatic quantum computation

Andrew M. Childs;Edward Farhi;John Preskill

600
Citations
Toward the first quantum simulation with quantum speedup.

Andrew M. Childs;Dmitri Maslov;Yun Seong Nam;Neil J. Ross;Neil J. Ross

585
Citations
Universal Computation by Multiparticle Quantum Walk

Andrew M. Childs;David Gosset;Zak Webb

522
Citations
On the Relationship Between Continuous- and Discrete-Time Quantum Walk

Andrew M. Childs

476
Citations
Hamiltonian Simulation with Nearly Optimal Dependence on all Parameters

Dominic W. Berry;Andrew M. Childs;Robin Kothari

415
Citations
Quantum algorithms for algebraic problems

Andrew M. Childs;Wim van Dam

415
Citations
Exponential improvement in precision for simulating sparse Hamiltonians

Dominic W. Berry;Andrew M. Childs;Andrew M. Childs;Richard Cleve;Richard Cleve;Robin Kothari;Robin Kothari

396
Citations
Quantum algorithm for systems of linear equations with exponentially improved dependence on precision

Andrew M. Childs;Robin Kothari;Rolando D. Somma

390
Citations
Exponential algorithmic speedup by quantum walk

Andrew M. Childs;Richard Cleve;Enrico Deotto;Edward Farhi

361
Citations
Constructing elliptic curve isogenies in quantum subexponential time

Andrew M. Childs;David Jao;Vladimir Soukharev

354
Citations
Quantum Algorithm for Systems of Linear Equations with Exponentially Improved Dependence on Precision

Andrew M. Childs;Robin Kothari;Rolando D. Somma

354
Citations
Hamiltonian simulation using linear combinations of unitary operations

Andrew M. Childs;Nathan Wiebe

322
Citations
Hamiltonian Simulation Using Linear Combinations of Unitary Operations

Nathan Wiebe;Andrew Childs

299
Citations
Secure assisted quantum computation

Andrew M. Childs

233
Citations
Any AND-OR Formula of Size $N$ Can Be Evaluated in Time $N^{1/2+o(1)}$ on a Quantum Computer

A. Ambainis;A. M. Childs;B. W. Reichardt;R. Špalek

230
Citations
Automated optimization of large quantum circuits with continuous parameters

Yunseong Nam;Neil J. Ross;Yuan Su;Andrew M. Childs

222
Citations
Efficient quantum algorithm for dissipative nonlinear differential equations.

Jin-Peng Liu;Herman Øie Kolden;Herman Øie Kolden;Hari K. Krovi;Nuno F. Loureiro

219
Citations
Quantum information and precision measurement

Andrew M. Childs;John Preskill;Joseph Renes

215
Citations
ANY AND-OR FORMULA OF SIZE N CAN BE EVALUATED IN TIME N1/2+o(1) ON A QUANTUM COMPUTER

A. Ambainis;A. M. Childs;B. W. Reichardt;R. Spalek

187
Citations
Theory of Trotter Error with Commutator Scaling

Andrew M. Childs;Yuan Su;Minh C. Tran;Nathan Wiebe;Nathan Wiebe;Nathan Wiebe

184
Citations
Black-box hamiltonian simulation and unitary implementation

Dominic W. Berry;Andrew M. Childs

183
Citations

Frequent Co-Authors

Debbie Leung University of Waterloo

Nathan Wiebe University of Toronto

Richard Cleve University of Waterloo

Edward Farhi MIT

Andris Ambainis University of Latvia

Dmitri Maslov IBM (United States)

Guifre Vidal Google (United States)

Isaac L. Chuang MIT

John Preskill California Institute of Technology

Frank Verstraete Ghent University

External Links

Wikipedia of Andrew M. Childs Personal website of Andrew M. Childs Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Exploring online degree options can be a smart move for those interested in computer science and related fields. Many universities now offer most in demand masters degrees fully online, helping graduates qualify for top roles in technology, analytics, and cybersecurity.

For students who need a quicker or more affordable path, consider 1 year associate degree programs online. These programs allow you to gain essential technical skills and often serve as a stepping stone to a bachelor's program or entry-level IT employment.

Affordability is often a concern, but many schools offer affordable online degree programs that minimize debt while still offering recognized credentials. Some online colleges are also welcoming to non-traditional students by offering flexible admission standards.

If your academic record has gaps, it’s worth exploring online graduate programs that accept 2.0 gpa. These institutions provide a second chance for students who want to pursue advanced studies and career growth despite a lower undergraduate GPA.