565 citations · 855 across the 26 of their papers we have counts for
26 papers
Theory and practice of Trotter product formulas for quantum chemistry
Pablo A. M. Casares, William Maxwell, Danial Motlagh +7
Trotter product formulas are a fundamental class of methods for Hamiltonian simulation, particularly attractive due to their low qubit requirements. However, they are often overloo…
Practical Estimation of Trotter Error for Hamiltonian Simulation
William Maxwell, Pablo A. M. Casares, Robert A. Lang +7
Trotter product formulas are a leading approach for Hamiltonian simulation on quantum computers, yet their practical performance has remained difficult to assess due to the challen…
Capabilities Ain't All You Need: Measuring Propensities in AI
Daniel Romero-Alvarado, Fernando Martínez-Plumed, Lorenzo Pacchiardi +11
AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired from Item Response Theory (IRT) being increasingly applied. Yet propensities - the te…
Quantum Algorithms for Photoreactivity in Cancer-Targeted Photosensitizers
Yanbing Zhou, Pablo A. M. Casares, Diksha Dhawan +5
Photodynamic therapy (PDT) is a targeted cancer treatment that uses light-activated photosensitizers to generate reactive oxygen species that selectively destroy tumor cells, gener…
Quantum algorithms to detect ODMR-active defects for quantum sensing applications
Pablo A. M. Casares, Yanbing Zhou, Utkarsh Azad +6
Spin defects in two-dimensional materials are a promising platform for quantum sensing. Simulating the defect's optical response and optically detected magnetic resonance (ODMR) co…
Fast simulations of X-ray absorption spectroscopy for battery materials on a quantum computer
Stepan Fomichev, Pablo A. M. Casares, Jay Soni +5
X-ray absorption spectroscopy (XAS) is a leading technique for understanding structural changes in advanced battery materials such as lithium-excess cathodes. However, extracting c…
Simulating near-infrared spectroscopy on a quantum computer for enhanced chemical detection
Ignacio Loaiza, Stepan Fomichev, Danial Motlagh +5
Near-infrared (NIR) spectroscopy is a non-invasive, low-cost, reagent-less, and rapid technique to measure chemical concentrations in a wide variety of sample types. However, extra…
General Scales Unlock AI Evaluation with Explanatory and Predictive Power
Lexin Zhou, Lorenzo Pacchiardi, Fernando Martínez-Plumed +23
Ensuring safe and effective use of AI requires understanding and anticipating its performance on novel tasks, from advanced scientific challenges to transformed workplace activitie…
Approximating exponentials of commutators by optimized product formulas
F. Casas, A. Escorihuela-Tomàs, P. A. Moreno Casares
Trotter product formulas constitute a cornerstone quantum Hamiltonian simulation technique. However, the efficient implementation of Hamiltonian evolution of nested commutators rem…
Simulating optically-active spin defects with a quantum computer
Jack S. Baker, Pablo A. M. Casares, Modjtaba Shokrian Zini +5
There is a pressing need for more accurate computational simulations of the opto-electronic properties of defects in materials to aid in the development of quantum sensing platform…
Quantum simulation of time-dependent Hamiltonians via commutator-free quasi-Magnus operators
Pablo Antonio Moreno Casares, Modjtaba Shokrian Zini, Juan Miguel Arrazola
Hamiltonian simulation is arguably the most fundamental application of quantum computers. The Magnus operator is a popular method for time-dependent Hamiltonian simulation in compu…
The hardness of quantum spin dynamics
Chae-Yeun Park, Pablo A. M. Casares, Juan Miguel Arrazola +1
Recent experiments demonstrated quantum computational advantage in random circuit sampling and Gaussian boson sampling. However, it is unclear whether these experiments can lead to…
Initial state preparation for quantum chemistry on quantum computers
Stepan Fomichev, Kasra Hejazi, Modjtaba Shokrian Zini +8
Quantum algorithms for ground-state energy estimation of chemical systems require a high-quality initial state. However, initial state preparation is commonly either neglected enti…
Grad DFT: a software library for machine learning enhanced density functional theory
Pablo A. M. Casares, Jack S. Baker, Matija Medvidovic +2
Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it s…
Quantum simulation of battery materials using ionic pseudopotentials
Modjtaba Shokrian Zini, Alain Delgado, Roberto dos Reis +4
Ionic pseudopotentials are widely used in classical simulations of materials to model the effective potential due to the nucleus and the core electrons. Modeling fewer electrons ex…
Fault-tolerant quantum algorithms
Pablo Antonio Moreno Casares
The framework of this thesis is fault-tolerant quantum algorithms. Grover's algorithm and quantum walks are described in Chapter 2. We start by highlighting the central role that r…
Parameter Estimation of Gravitational Waves with a Quantum Metropolis Algorithm
Gabriel Escrig, Roberto Campos, Pablo A. M. Casares +1
After the first detection of a gravitational wave in 2015, the number of successes achieved by this innovative way of looking through the universe has not stopped growing. However,…
Quantum Metropolis Solver: A Quantum Walks Approach to Optimization Problems
Roberto Campos, Pablo A M Casares, M A Martin-Delgado
The efficient resolution of optimization problems is one of the key issues in today's industry. This task relies mainly on classical algorithms that present scalability problems an…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
Simulating key properties of lithium-ion batteries with a fault-tolerant quantum computer
Alain Delgado, Pablo A. M. Casares, Roberto dos Reis +9
There is a pressing need to develop new rechargeable battery technologies that can offer higher energy storage, faster charging, and lower costs. Despite the success of existing me…
TFermion: A non-Clifford gate cost assessment library of quantum phase estimation algorithms for quantum chemistry
Pablo A. M. Casares, Roberto Campos, M. A. Martin-Delgado
Quantum Phase Estimation is one of the most useful quantum computing algorithms for quantum chemistry and as such, significant effort has been devoted to designing efficient implem…
QFold: Quantum Walks and Deep Learning to Solve Protein Folding
P A M Casares, Roberto Campos, M A Martin-Delgado
Predicting the 3D structure of proteins is one of the most important problems in current biochemical research. In this article, we explain how to combine recent deep learning advan…
Circuit implementation of bucket brigade qRAM for quantum state preparation
Pablo Antonio Moreno Casares
In this short review I aim to explain how we can construct a circuit implementation of the bucketbrigade qRAM first proposed in [1]. Used with classical data, this qRAM model can b…
A quantum active learning algorithm for sampling against adversarial attacks
P. A. M. Casares, M. A. Martin-Delgado
Adversarial attacks represent a serious menace for learning algorithms and may compromise the security of future autonomous systems. A theorem by Khoury and Hadfield-Menell (KH), p…