TensorCircuit is an open source quantum circuit simulator based on tensor network
contraction, designed for speed, flexibility and code efficiency. Written purely in Python, and …

This work brings the leading accuracy, sample efficiency, and robustness of deep
equivariant neural networks to the extreme computational scale. This is achieved through a …

Automatic ICD coding is defined as assigning disease codes to electronic medical records
(EMRs). Existing methods usually apply label attention with code representations to match …

From the most fundamental to the most practical side of density functional theory (DFT),
Kohn–Sham inversions (iKS) can contribute to the development of functional approximations …

Monitored quantum circuits (MRCs) exhibit a measurement-induced phase transition
between area-law and volume-law entanglement scaling. MRCs with a conserved charge …

In this paper, we eliminate the classical outer learning loop of the quantum approximate
optimization algorithm (QAOA) and present a strategy to find good parameters for QAOA …

We present the first study of baryon-baryon interactions in the continuum limit of lattice QCD,
finding unexpectedly large lattice artifacts. Specifically, we determine the binding energy of …

We develop an algorithmic framework for contracting tensor networks and demonstrate its
power by classically simulating quantum computation of sizes previously deemed out of …

We introduce a general method of performing Residual Network inference and learning in
the JPEG transform domain that allows the network to consume compressed images as …

The modern study of astrophysical transients has been transformed by an exponentially
growing volume of data. Within the last decade, the transient discovery rate has increased …