Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Manas Sajjan"'
Publikováno v:
Natural Sciences, Vol 3, Iss 4, Pp n/a-n/a (2023)
Abstract Analyzing phase transitions using the inherent geometrical attributes of a system has garnered enormous interest over the past few decades. The usual candidate often used for investigation is graphene—the most celebrated material among the
Externí odkaz:
https://doaj.org/article/926fae19dcff4126adfd0962975bbb3a
Publikováno v:
Physical Review Research, Vol 6, Iss 1, p 013010 (2024)
The random sampling task performed by Google's Sycamore processor gave us a glimpse of the “quantum supremacy era.” This has definitely shed some light on the power of random quantum circuits in this abstract task of sampling outputs from the (ps
Externí odkaz:
https://doaj.org/article/1a4810f0afa7435f8df90e1189aeb860
Publikováno v:
Mathematics, Vol 11, Iss 22, p 4678 (2023)
Efficient methods for encoding and compression are likely to pave the way toward the problem of efficient trainability on higher-dimensional Hilbert spaces, overcoming issues of barren plateaus. Here, we propose an alternative approach to variational
Externí odkaz:
https://doaj.org/article/e6a4716f87964ab4aa281ed3b8a0cd25
Autor:
Chung-You Shih, Sainath Motlakunta, Nikhil Kotibhaskar, Manas Sajjan, Roland Hablützel, Rajibul Islam
Publikováno v:
npj Quantum Information, Vol 7, Iss 1, Pp 1-8 (2021)
Abstract High-precision, individually programmable manipulation of quantum particles is crucial for scaling up quantum information processing (QIP) systems such as laser-cooled trapped-ions. However, restricting undesirable “crosstalk” in optical
Externí odkaz:
https://doaj.org/article/27c99214c1ed4242973196eb0db746c9
Publikováno v:
Physical Review Research, Vol 5, Iss 1, p 013146 (2023)
We introduce and analytically illustrate that hitherto unexplored imaginary components of out-of-time order correlators can provide unprecedented insight into the information scrambling capacity of a graph neural network. Furthermore, we demonstrate
Externí odkaz:
https://doaj.org/article/4fbade3832ae40ca8e018e9dafdc4c47
Publikováno v:
Symmetry, Vol 14, Iss 3, p 457 (2022)
We explore how to build quantum circuits that compute the lowest energy state corresponding to a given Hamiltonian within a symmetry subspace by explicitly encoding it into the circuit. We create an explicit unitary and a variationally trained unitar
Externí odkaz:
https://doaj.org/article/e956d4ebb46548ccb00b4fb1900b1ad4
Publikováno v:
Physical Chemistry Chemical Physics. 24:28870-28877
Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct with high fidelity, the quant
Publikováno v:
Journal of the American Chemical Society. 143:18426-18445
Quantum machine-learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure calculatio
Autor:
Manas Sajjan, Junxu Li, Raja Selvarajan, Shree Hari Sureshbabu, Sumit Suresh Kale, Rishabh Gupta, Vinit Singh, Sabre Kais
Publikováno v:
Chemical Society reviews. 51(15)
Machine learning (ML) has emerged into formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In the recent years, it is safe to conclude th
Publikováno v:
The Journal of Physical Chemistry A. 125:5448-5455
We report switching of molecular conductance at finite bias in a binuclear organometallic complex and its cation which were previously experimentally analyzed at low voltages to see the signature of Kondo resonance. The variational reduced density ma