Student Assistant - Condensed Matter Physics
About The Position
The Condensed Matter Physics Department is seeking a Part-Time - Student Assistant to work on the following project: Tensor networks have emerged as a powerful tool to simulate quantum many-body systems in equilibrium at zero and finite temperature, but also for dynamical simulations of correlated quantum systems. The exponential thermal renormalization group (XTRG, Chen et al., PRX 2018) was introduced as a simple transparent approach for thermal simulations that traverses energy scales exponentially by doubling the Gibbs state with itself. The project intends to explore a similar approach in the real-time domain. Benchmarks will be performed against Trotterization for short-ranged systems, but also for longer-range systems based on exact analytic solutions. The employed toolbox is the open-source tensor library QSpace (v4) which is a highly optimized C++ library embedded into Matlab. With this, the coding can directly focus on the project within Matlab, yet with full access to physical symmetries for numerical efficiency. Hands-on familiarity with numerical quantum-many-body techniques and tensor network simulations is required, even if not with QSpace itself yet, thus likely requiring a senior graduate student. The project duration is limited to 10 weeks starting mid June to align with summer interns at the Brookhaven National Laboratory for 2026.
Requirements
- Active enrollment in an undergraduate or graduate level degree program in Computer Science, Mathematics, Physics, Materials Science or related.
- The candidate may not exceed 1 semester past graduation from their program.
- Hands-on experience on tensor network methods and algorithms
- General overall understanding of quantum-many-body systems in lattice models
- Significant computational experience
Nice To Haves
- Matlab environment
- HPC Cluster environment
Responsibilities
- Familiarize themselves with tensor network setups within QSpace environment
- Thorough understanding of XTRG (2018), to extend to real-time domain
- Develop proof of principle demonstrations and benchmark against conventional approaches
- Summarize results in paper
Benefits
- Comprehensive employee benefits program
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What This Job Offers
Job Type
Part-time
Career Level
Senior
Education Level
No Education Listed
