Research
In-depth analysis of the latest academic papers, breakthroughs, and experimental results in quantum computing.
Quantum mechanics on the line with two origins
arXiv:2607.26080v1 Announce Type: new Abstract: We study scalar and spinorial quantum dynamics on the standard line with two origins, \[ \Ltwo=(\R_1\sqcup\R_2)/...
Qubit-qubit-qutrit quantum correlations in $H \to f \bar f V$
arXiv:2607.26122v1 Announce Type: new Abstract: We perform an extensive analysis of the quantum correlations carried by the qubit-qubit-qutrit pure state arisin...
A Difference Operator Approach to Quantum Random Walks: Parseval Identity, Krawtchouk Matrices, and Hermite Limits
arXiv:2607.24837v1 Announce Type: new Abstract: We introduce a discrete difference operator D_k to study the one-dimensional quantum random walk (QRW) with the...
Can a quantum circuit detect the Unruh effect?
arXiv:2607.24836v1 Announce Type: new Abstract: The Unruh effect predicts that an accelerating observer perceives the Minkowski vacuum as a thermal bath, yet di...
Closed-Form Expectation Values of the Damped Kerr Oscillator
arXiv:2607.24842v1 Announce Type: new Abstract: We derive a closed-form analytical expression for the expectation values of a damped Kerr nonlinear oscillator i...
Unitary designs from perturbed time evolutions of a chaotic Hamiltonian
arXiv:2607.24851v1 Announce Type: new Abstract: Unitary designs provide efficient substitutes for Haar-random unitaries in quantum information processing, rando...
Wave-functional formulation of dissipative CSL models
arXiv:2607.24853v1 Announce Type: new Abstract: We formulate minimal and dissipative Continuous Spontaneous Localization (CSL) dynamics in the functional Schr\"...
Bias-preserving cat-cat CNOT gate via vacuum-conditional beam-splitter
arXiv:2607.22852v1 Announce Type: new Abstract: Cat qubits can exhibit strong noise bias due to their exponentially enhanced bit-flip times and only polynomiall...
Machine Learning of Quantum Entanglement from Noisy Measurements
arXiv:2607.22853v1 Announce Type: new Abstract: In this work, we investigate the application of Machine Learning (ML) algorithms to the identification and quant...