10 citations · 23 across the 8 of their papers we have counts for
7 papers · 1 filter
Entanglement of superpositions in zero-energy subspace: insights from stabilizer theory
Konstantin Antipin, Richik Sengupta
Exact zero-energy eigenstates built from entangled dimers have recently been found in a large class of spin Hamiltonians. While the individual states have a simple structure, their…
High order schemes for solving partial differential equations on a quantum computer
Boris Arseniev, Dmitry Guskov, Richik Sengupta +1
We explore the utilization of higher-order discretization techniques in optimizing the gate count needed for quantum computer based solutions of partial differential equations. To…
Tridiagonal matrix decomposition for Hamiltonian simulation on a quantum computer
Boris Arseniev, Dmitry Guskov, Richik Sengupta +2
The construction of quantum circuits to simulate Hamiltonian evolution is central to many quantum algorithms. State-of-the-art circuits are based on oracles whose implementation is…
On Translation-Invariant Matrix Product States and advances in MPS representations of the -state
Petr Klimov, Richik Sengupta, Jacob Biamonte
This work is devoted to the study Translation-Invariant (TI) Matrix Product State (MPS) representations of quantum states with periodic boundary conditions (PBC). We pursue two dir…
Tensor networks in machine learning
Richik Sengupta, Soumik Adhikary, Ivan Oseledets +1
A tensor network is a type of decomposition used to express and approximate large arrays of data. A given data-set, quantum state or higher dimensional multi-linear map is factored…
Ion native variational ansatz for quantum approximate optimization
Daniil Rabinovich, Soumik Adhikary, Ernesto Campos +6
Variational quantum algorithms involve training parameterized quantum circuits using a classical co-processor. An important variational algorithm, designed for combinatorial optimi…
Progress towards analytically optimal angles in quantum approximate optimisation
D. Rabinovich, R. Sengupta, E. Campos +2
The Quantum Approximate Optimisation Algorithm is a layer, time-variable split operator method executed on a quantum processor and driven to convergence by classical outer loop…