Check out the tools and examples in BAND Framework v0.2! And stay tuned for additional capabilities in v0.3!

See the BAND Manifesto in Journal of Physics G! (or on arXiv)

Nuclear physicists seek an accurate description of the properties of atomic nuclei, collisions between nuclei, and extreme environments such as the first few seconds of our universe or the interior of a neutron star. These situations involve many particles interacting through complex forces. They’re each described by a number of different models: these typically do a good job of explaining the results of experiments that have already occurred. The models don’t do as well predicting what will happen in future experiments or in environments that are inaccessible here on Earth.

The Bayesian Analysis of Nuclear Dynamics (BAND) Framework will use advanced statistical methods to produce forecasts for as-yet-unexplored situations that combine nuclear-physics models in an optimal way. These will be more reliable than the predictions of any individual model. BAND’s forefront computer codes will be widely available and will facilitate the design of nuclear-physics experiments that can deliver the largest gain in understanding. The adoption of BAND’s tools in other sciences dealing with “model uncertainty” could spur broad scientific innovation. Undergraduate and graduate students working on BAND will gain a broad range of technical skills in data science, machine learning, nuclear physics, and high-performance computing.

BAND Code of Conduct

BAND is committed to fostering a safe, diverse, inclusive, and equitable environment that values mutual respect and personal integrity. Therefore, all participants in BAND activities will conduct themselves in a welcoming and professional manner, treating one another respectfully and considerately. This is particularly important in interdisciplinary work that brings together collaborators from different scientific backgrounds and cultures. Creating such a culture–one that is collegial, inclusive, and professional–is the responsibility of all collaboration members and meeting participants.

Those participating in BAND activities shall not discriminate against, harass, or bully others. If you observe inappropriate comments or actions and personal intervention seems appropriate and safe, you are encouraged to intervene in ways that are, insofar as it is possible, considerate of all parties involved. BAND members and meeting participants will not discriminate against, act in an inappropriate way, or make inappropriate statements related to aspects of each other’s identity such as age, race, ethnicity, perceived or actual social class, sexual orientation, gender identity, gender expression, marital status, nationality, political affiliation, religion, ability status, and educational background. No kind of harassment (including sexual harassment) or bullying will be tolerated.

Bullying is unwelcome, aggressive behavior involving the use of influence, threat, intimidation, or coercion to dominate others. Harassment includes but is not limited to: inappropriate or intimidating behavior and language, unwelcome jokes or comments, unwanted touching or attention, offensive images, photography without permission, and stalking. Sexual harassment is unwelcome sexual advances, requests for sexual favors, and other verbal or physical conduct of a sexual nature that creates an intimidating, hostile, or offensive environment.

Violations of this code of conduct policy should be reported to meeting organizers and/or the BAND “Community Leaders”: Daniel Phillips (, Dick Furnstahl (, Frederi Viens (, and Stefan Wild ( Sanctions may range from verbal warning, to ejection from the meeting, to a suspension from future BAND activities, to the notification of appropriate local authorities. Retaliation for complaints of inappropriate conduct will not be tolerated and will result in an escalated sanction.

News ( see all News)

August 14, 2023

The third BAND annual retreat has successfully concluded! The retreat was held from August 8 - 9 at the Ohio University Dublin Integrated Education Center. During the retreat, BAND members gathered to review the progress made for various projects and share exciting updates in software development. Prior to the retreat on August 7, the external Advisory Board met with BAND members. We greatly appreciate the Board for their advice and support for BAND!

June 29, 2023

BAND members Pablo Giuliani, Kyle Godbey, Frederi Viens, and Alexandra Semposki co-organized the FRIB-TA Summer School on Practical Uncertainty Quantification and Emulator Development in Nuclear Physics. The school ran from June 26th to June 28th at the Facility for Rare Isotope Beams on the campus of Michigan State University.

June 9, 2023

Postdoc Sunil Jaiswal has joined the BAND team! Sunil received his Ph.D. from the Tata Institute of Fundamental Research in Mumbai, India. He will be working at the Ohio State University with Dick Furnstahl, Ulrich Heinz, and Matt Pratola.

May 26, 2023

ISNET-9, held at Washington University in St. Louis from May 23 to 26, 2023, featured presentations by BAND researchers: Ozge Sürer, Dan Liyanage, Witek Nazarewicz, Dick Furnstahl, Pablo Giuliani, Daniel Odell, and Kyle Godbey, and former BAND Fellow Jason Bub. Slides are available at the ISNET-9 website.

May 22, 2023

BAND Camp 2023 was a great success! It was held just before ISNET-9 at Washington University in St. Louis on May 22, 2023, and featured interactive presentations (with Python code via Google Colab) by BAND researchers Matt Pratola, Moses Chan, Ozge Sürer, Daniel Odell, Pablo Giuliani, Alexandra Semposki, John Yanotty, Kyle Godbey, Witek Nazarewicz, and Dick Furnstahl. Slides and videos are available here.

May 16, 2023

Double congratulations to BAND graduate student Moses Chan! First off, the paper he wrote "Constructing a simulation surrogate with missing output" together with fellow BAND members Matt Plumlee and Stefan Wild, was published earlier this month in Technometrics. Second, in Fall 2023 Moses will join the faculty at Northwestern as an Assistant Professor of Instruction; he will spearhead their Data Science & Engineering program.

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