Supriyo Datta
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View article: Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm
Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm Open
Reducing energy consumption has become a pressing need for modern machine learning, which has achieved many of its most impressive results by scaling to larger and more energy-consumptive neural networks. Unfortunately, the main algorithm …
View article: Aging of colloidal gels in microgravity
Aging of colloidal gels in microgravity Open
We study the aging of colloidal gels using light microscopy movies of depletion gels from the International Space Station. Under such microgravity conditions, we observe a slowdown in particle dynamics consistent with gel aging. Stronger a…
View article: Connecting physics to systems with modular spin-circuits
Connecting physics to systems with modular spin-circuits Open
An emerging paradigm in modern electronics is that of CMOS+ $${\mathsf{X}}$$ requiring the integration of standard CMOS technology with novel materials and technologies denoted by $${\mathsf{X}}$$ . In this context, a crucial challenge…
View article: An Empirical Assessment of India’s Position in Global Sustainable Bond Market
An Empirical Assessment of India’s Position in Global Sustainable Bond Market Open
This study aims to examine India's position in the global green bond market and identify areas for improvement to develop its sustainable finance sector. Analysing data from the Luxembourg Green Exchange (1999-2024) and Indian market sourc…
View article: Connecting physics to systems with modular spin-circuits
Connecting physics to systems with modular spin-circuits Open
An emerging paradigm in modern electronics is that of CMOS + $\sf X$ requiring the integration of standard CMOS technology with novel materials and technologies denoted by $\sf X$. In this context, a crucial challenge is to develop accurat…
View article: Roadmap for unconventional computing with nanotechnology
Roadmap for unconventional computing with nanotechnology Open
In the ‘Beyond Moore’s Law’ era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benef…
View article: Heisenberg machines with programmable spin-circuits
Heisenberg machines with programmable spin-circuits Open
We show that we can harness two recent experimental developments to build a compact hardware emulator for the classical Heisenberg model in statistical physics. The first is the demonstration of spin-diffusion lengths in excess of microns …
View article: Accelerated quantum Monte Carlo with probabilistic computers
Accelerated quantum Monte Carlo with probabilistic computers Open
Quantum Monte Carlo (QMC) techniques are widely used in a variety of scientific problems and much work has been dedicated to developing optimized algorithms that can accelerate QMC on standard processors (CPU). With the advent of various s…
View article: A Full-Stack View of Probabilistic Computing With p-Bits: Devices, Architectures, and Algorithms
A Full-Stack View of Probabilistic Computing With p-Bits: Devices, Architectures, and Algorithms Open
The transistor celebrated its 75th birthday in 2022. The continued scaling of the transistor defined by Moore’s law continues, albeit at a slower pace. Meanwhile, computing demands and energy consumption required by modern artificial intel…
View article: A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms
A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms Open
The transistor celebrated its 75${}^\text{th}$ birthday in 2022. The continued scaling of the transistor defined by Moore's Law continues, albeit at a slower pace. Meanwhile, computing demands and energy consumption required by modern arti…
View article: Roadmap for Unconventional Computing with Nanotechnology
Roadmap for Unconventional Computing with Nanotechnology Open
In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benef…
View article: Emulating Quantum Circuits With Generalized Ising Machines
Emulating Quantum Circuits With Generalized Ising Machines Open
The primary objective of this paper is to present an exact and general procedure for mapping any sequence of quantum gates onto a network of probabilistic p-bits which can take on one of two values 0 and 1. The first p-bits represent the …
View article: Multifunctional Spin Logic Operations in Graphene Spin Circuits
Multifunctional Spin Logic Operations in Graphene Spin Circuits Open
Spin-based computing, combining logic and nonvolatile magnetic memory, is promising for emerg-ing information technologies. However, the realization of a universal spin logic operation, representing a reconfigurable building block with all…
View article: An Efficient MCMC Approach to Energy Function Optimization in Protein Structure Prediction
An Efficient MCMC Approach to Energy Function Optimization in Protein Structure Prediction Open
Protein structure prediction is a critical problem linked to drug design, mutation detection, and protein synthesis, among other applications. To this end, evolutionary data has been used to build contact maps which are traditionally minim…
View article: Accelerated Quantum Monte Carlo with Probabilistic Computers
Accelerated Quantum Monte Carlo with Probabilistic Computers Open
Quantum Monte Carlo (QMC) techniques are widely used in a variety of scientific problems and much work has been dedicated to developing optimized algorithms that can accelerate QMC on standard processors (CPU). With the advent of various s…
View article: Hardware-Aware <i>In Situ</i> Learning Based on Stochastic Magnetic Tunnel Junctions
Hardware-Aware <i>In Situ</i> Learning Based on Stochastic Magnetic Tunnel Junctions Open
One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics is a promising catalyst for this field with the capabilities…
View article: Can Negative Capacitance Induce Superconductivity?
Can Negative Capacitance Induce Superconductivity? Open
Superconductivity was originally observed in 3D metals caused by an effective attraction between electrons mediated by the electron-phonon interaction. Since then there has been a lot of work on 2D conductors including the possibility of a…
View article: Probabilistic computing with p-bits
Probabilistic computing with p-bits Open
Digital computers store information in the form of bits that can take on one of two values 0 and 1, while quantum computers are based on qubits that are described by a complex wavefunction, whose squared magnitude gives the probability of …
View article: Benchmarking a Probabilistic Coprocessor
Benchmarking a Probabilistic Coprocessor Open
Computation in the past decades has been driven by deterministic computers based on classical deterministic bits. Recently, alternative computing paradigms and domain-based computing like quantum computing and probabilistic computing have …
View article: Multifunctional Spin Logic Gates In Graphene Spin Circuits
Multifunctional Spin Logic Gates In Graphene Spin Circuits Open
All-spin-based computing combining logic and nonvolatile magnetic memory is promising for emerging information technologies. However, the realization of a universal spin logic operation representing a reconfigurable building block with all…
View article: Perspective: Probabilistic computing with p-bits.
Perspective: Probabilistic computing with p-bits. Open
Digital computers store information in the form of $bits$ that can take on one of two values $0$ and $1$, while quantum computers are based on $qubits$ that are described by a complex wavefunction whose squared magnitude gives the probabil…
View article: Dialogue Concerning the Two Chief Computing Systems: Imagine yourself on a flight talking to an engineer about a scheme that straddles classical and quantum
Dialogue Concerning the Two Chief Computing Systems: Imagine yourself on a flight talking to an engineer about a scheme that straddles classical and quantum Open
that could one day lead to a momentous transition: from deterministic computing systems, based on classical physics, to quantum computing systems, which exploit the weird and wacky probabilistic rules of quantum physics.Many commentators h…
View article: Hardware-aware $in \ situ$ Boltzmann machine learning using stochastic magnetic tunnel junctions
Hardware-aware $in \ situ$ Boltzmann machine learning using stochastic magnetic tunnel junctions Open
One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics is a promising catalyst for this field with the capabilities…
View article: A Unified Framework for Spin-Charge Interconversion in Spin-Orbit Materials
A Unified Framework for Spin-Charge Interconversion in Spin-Orbit Materials Open
Materials with spin-orbit coupling are of great current interest for various spintronics applications due to the efficient electrical generation and detection of electron spins. Over the past decade, a large number of materials have been s…
View article: Hardware implementation of Bayesian network building blocks with stochastic spintronic devices
Hardware implementation of Bayesian network building blocks with stochastic spintronic devices Open
Bayesian networks are powerful statistical models to understand causal relationships in real-world probabilistic problems such as diagnosis, forecasting, computer vision, etc. For systems that involve complex causal dependencies among many…
View article: Emulating Quantum Interference with Generalized Ising Machines
Emulating Quantum Interference with Generalized Ising Machines Open
The primary objective of this paper is to present an exact and general procedure for mapping any sequence of quantum gates onto a network of probabilistic p-bits which can take on one of two values 0 and 1. The first $n$ p-bits represent t…
View article: Hardware implementation of Bayesian network building blocks with stochastic spintronic devices
Hardware implementation of Bayesian network building blocks with stochastic spintronic devices Open
Bayesian networks are powerful statistical models to understand causal relationships in real-world probabilistic problems such as diagnosis, forecasting, computer vision, etc. For systems that involve complex causal dependencies among many…