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Anant Agarwal is a computer scientist and electrical engineer whose work includes computer architecture, multicore processors and circuit education. MIT's departmental profile lists computer architecture among his research areas, while his CSAIL profile describes work involving multicore computing and authorship of a circuits textbook.^[ref]

His identified MIT faculty page links an external portrait of Anant Agarwal.

The MIT lecture State and Memory by Anant Agarwal and Jeffrey Lang, jointly credited with Jeffrey Lang, connects analog stored state to computer memory. A capacitor can summarize prior input by one state quantity, such as stored electric charge $q=C{v}_C$; digital storage then adds a rule for distinguishing logical values. The slides explicitly introduce capacitor state, zero-input response, zero-state response and a one-bit memory abstraction.^[ref]

For an original physical-memory example, let a $1\mathrm{nF}$ capacitor initially hold $3\mathrm{V}$ and leak through a $1\mathrm{M\Omega }$ resistor. With no driving input,If a stipulated readout interprets values above $2\mathrm{V}$ as the stored high state, the ideal decay reaches that threshold afterThe initial stored electric charge is $3\mathrm{nC}$, but the logical interpretation also depends on leakage, the elapsed time and the decision threshold. This is a teaching model, not a specification for a particular memory chip.

The example exposes why merely retaining some electric charge is different from reliably retaining a bit. A practical memory circuit must preserve distinguishable states over the required interval and allow the state to be read. Agarwal and Lang's lecture uses the state concept to connect the circuit's dynamics with that information-storage task.

Jeffrey Lang is an electrical engineer whose work concerns electromechanical conversion power balance, control and small-scale devices. MIT's Research Laboratory of Electronics identifies the same professor as Jeffrey H. Lang and describes research on electric motors, electrical generators and microelectromechanical systems, together with teaching in circuits and electromagnetism.^[ref]

The identified MIT profile provides an externally hosted portrait of Jeffrey H. Lang.

For an original motor-scale illustration, a shaft delivering torque $\tau =2\mathrm{mN}\mathrm{m}$ at angular velocity $\omega =1000\mathrm{rad}{\mathrm{s}}^{-1}$ delivers $P_m=\tau \omega =2\mathrm{W}$. If electrical input is $3\mathrm{W}$ and the operating point is steady, the remaining $1\mathrm{W}$ must be accounted for by losses or another specified output. During acceleration some input can instead increase rotational kinetic energy. Reporting only shaft speed would not establish either output power or conversion efficiency.

With Anant Agarwal, Lang is credited on the MIT course material State and Memory by Anant Agarwal and Jeffrey Lang. It explains how a capacitor's state summarizes the part of past input needed to predict its future response.^[ref] For a series RC circuit with a constant later input $V_f$,Two different earlier input histories that leave the same initial capacitor electric potential difference give the same subsequent response under the same future input. For stipulated $RC=1\mathrm{ms}$, $v_C(0)=1\mathrm{V}$ and $V_f=3\mathrm{V}$, the value after one time constant is $3-2/e\approx 2.2642\mathrm{V}$. This original numerical example shows what it means for the state to retain enough of the past without retaining the entire waveform.