Nilin Abrahamsen
nilin@berkeley.edu
The Simons Institute of Computing
Melvin Calvin Lab, office 314
Berkeley, CA 90720
I am a postdoctoral researcher at the Simons Institute of Computing at UC Berkeley.
I work on scientific computing and machine learning approaches to scientific problems. In my current research we use a neural network Ansatz to solve the SchrÃ¶dringer equation for ab initio quantum chemistry simulations.
I am mentored by Lin Lin.
I graduated my PhD from MIT Mathematics in 2021 under the supervision of Peter Shor and Jonathan Kelner.
Papers

Entanglement area law for 1D gauge theories and bosonic systems
Nilin Abrahamsen, Yuan Su, Yu Tong, Nathan Wiebe
To appear in Physical Review A.
Physical review A, Vol. 108, Iss. 4 â€” October 2023. 
Efficient antisymmetrization of a neural network layer by taming the sign problem
Nilin Abrahamsen, Lin Lin.
J. Mach. Learn., 2 (2023), pp. 211240. 
Simple and deterministic spectral concentration bound for local Hamiltonians
Nilin Abrahamsen
To appear in Quantum Information and Computation 
Inventing art styles with no artistic training data
Nilin Abrahamsen and Jiahao Yao.
Preprint. 
Antisymmetric Barron functions and their approximation with sums of determinants
Nilin Abrahamsen and Lin Lin.
Preprint. 
Convergence of stochastic gradient descent on parameterized sphere with applications to variational Monte Carlo simulation
with Zhiyan Ding, Gil Goldshlager, Lin Lin.  Solving degenerate 2D frustrationfree spin systems in subexponential time

A polynomialtime algorithm for ground states of spin trees
Quantum Information Processing (QIP) 2020. 
Sparse Gaussian ICA
Nilin Abrahamsen and Philippe Rigollet.